CN108595449A - The structure and application process of dispatch automated system knowledge mapping - Google Patents
The structure and application process of dispatch automated system knowledge mapping Download PDFInfo
- Publication number
- CN108595449A CN108595449A CN201711180687.1A CN201711180687A CN108595449A CN 108595449 A CN108595449 A CN 108595449A CN 201711180687 A CN201711180687 A CN 201711180687A CN 108595449 A CN108595449 A CN 108595449A
- Authority
- CN
- China
- Prior art keywords
- entity
- relationship
- knowledge mapping
- knowledge
- service
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000013507 mapping Methods 0.000 title claims abstract description 101
- 238000000034 method Methods 0.000 title claims abstract description 71
- 230000008569 process Effects 0.000 title claims abstract description 58
- 238000012423 maintenance Methods 0.000 claims abstract description 6
- 238000007726 management method Methods 0.000 claims description 35
- 238000000605 extraction Methods 0.000 claims description 7
- 230000008520 organization Effects 0.000 claims description 7
- 230000007246 mechanism Effects 0.000 claims description 6
- 238000004140 cleaning Methods 0.000 claims description 4
- 230000008030 elimination Effects 0.000 claims description 4
- 238000003379 elimination reaction Methods 0.000 claims description 4
- 238000004891 communication Methods 0.000 claims description 3
- 230000004927 fusion Effects 0.000 claims description 3
- 230000010354 integration Effects 0.000 claims description 3
- 238000012549 training Methods 0.000 claims description 3
- 238000011160 research Methods 0.000 claims description 2
- 230000006870 function Effects 0.000 description 15
- 238000010276 construction Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000001228 spectrum Methods 0.000 description 4
- 230000005540 biological transmission Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000001747 exhibiting effect Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000007257 malfunction Effects 0.000 description 1
- 230000002688 persistence Effects 0.000 description 1
- 238000012827 research and development Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention belongs to dispatch automated system field more particularly to a kind of structures and application process of dispatch automated system knowledge mapping.Described method includes following steps：1, the structure of knowledge mapping：Using the bottom-up and top-down method being combined, the knowledge mapping of intelligent grid Dispatching Control System basic platform and detailed service logic is built；2, the storage and maintenance of knowledge；3, the displaying and application of knowledge mapping：The knowledge mapping of the basic platform of front page layout display systems and detailed professional knowledge collection of illustrative plates, basic platform shows that general frame knowledge, the knowledge mapping of service logic show detailed logic relationship.Abstract dispatch automated system professional knowledge is showed in a manner of patterned, user is allowed to be visually known the professional knowledge of whole system by the knowledge mapping that the present invention is built.User can operate corresponding entity simultaneously, selectively check the professional knowledge oneself being concerned about, have very strong interactivity and availability.
Description
Technical field
The invention belongs to dispatch automated system field more particularly to a kind of structures of dispatch automated system knowledge mapping
With application process.
Background technology
With the development of all kinds of business of power grid, dispatch automated system types of applications is more and more, and professional knowledge is increasingly
It is complicated.Related service personnel only understand local professional knowledge mostly, and do not know associated service logic, only seldom
Number expert grade personnel, which could have entire operation flow, clearly to be recognized.Therefore work as complicated service logic when something goes wrong, need
Each business personnel is transferred temporarily, cleared all service logic relationships, be possible to find out the reason of causing problem.And if
Set up the knowledge mapping of entire dispatch automated system related service, so that it may with the related service expressed by knowledge mapping
Logic very clearly inquires all operations and data flow, to find out it is all there may be mistake reason.
The concept of knowledge mapping was proposed that Google wants the base in knowledge mapping project in 2012 at first by Google
On plinth, the intelligent search engine of a new generation is built.The thought of the search engine be the entity that all kinds of knowledge are obtained from webpage,
Incidence relation between attribute information and each entity, to establish the semantic network of knowledge.Traditional search engine is all base
It in the search of character string, rather than is scanned for according to corresponding semantic information, therefore traditional search engine may be searched for
Go out the information with semantic wide of the mark, and includes only the character string, and the search of knowledge based collection of illustrative plates is to be based on semantic analysis
, thus search for more accurate.
The structure of knowledge mapping has very high researching value for the displaying of knowledge with retrieval, at home Baidu and search dog
It is proposed " intimate " and " know cube " respectively to improve its search quality.Tsinghua University establish first extensive Chinese and English across
Linguistry collection of illustrative plates XLore, the Chinese Academy of Sciences have developed the prototype of " people cube, knows cube thing cube " on the basis of open network
System.
Looking into for Chinese knowledge mapping construction method and knowledge based collection of illustrative plates based on multi-source data was introduced in the prior art
Inquiry method.In the power system, there is presently no the relevant applications of knowledge mapping.Many knowledge in dispatch automated system are all
It is to be stored in the head of expert in the form of experience, or sporadically deposit in systems, few people can grasp institute comprehensively
Some professional knowledge.If relying solely on method of the Internet company based on semantic network, due to lacking power specialty knowledge background,
Causing the knowledge mapping established to occur, business is complete, the inadequate and professional not strong problem of accuracy.Therefore electric system from
Dynamicization field, for the related service logic of dispatch automated system, the method for proposing structure knowledge mapping establishes Department of Automation
The knowledge mapping of system is convenient for summary, search and the propagation of knowledge, has very high researching value.
Invention content
For the problems in background technology, the purpose of the present invention is to provide a kind of dispatch automated system knowledge mappings
Structure and application process.
To achieve the goals above, the following technical solutions are proposed by the present invention：
A kind of structure and application process of dispatch automated system knowledge mapping, it is characterised in that：
It the described method comprises the following steps：
(1) structure of knowledge mapping：The basis that intelligent grid Dispatching Control System is built using bottom-up mode is flat
The knowledge mapping of platform builds the knowledge graph of the detailed service logic of intelligent grid Dispatching Control System using top-down mode
Spectrum；
(2) storage and maintenance of knowledge mapping：The data of knowledge mapping are stored based on historical data base, knowledge mapping
Safeguard knowledge based collection of illustrative plates displaying interface carry out；
(3) displaying and application of knowledge mapping：The basic platform of front page layout display systems and detailed professional knowledge figure
Spectrum, the general frame knowledge of the knowledge mapping displaying intelligent grid Dispatching Control System of basic platform, the knowledge graph of service logic
The detailed logic relationship of spectrum displaying intelligent grid Dispatching Control System.
Further, in step (1), include altogether six major class function modules in the basic platform, be respectively：Platform pipe
Reason, historical data base, real-time data base, messaging bus, service bus and public service；
The platform management realizes the management to whole system, including application management, process pipe by a set of management tool
Reason, Clock management, log management and timing task management；
The historical data base is mainly used to preserve grid equipment, parameter, historical statistical information；
The real-time data base is used for providing efficient real time data access service；
The messaging bus and service bus are used to provide reliable general information exchange mechanism and wide-area services mechanism, real
Safe and efficient data communication and application integration between control centre inside existing control centre；
The public service be application exploitation and it is integrated one group of generic service is provided, including graphical services, file service,
Rights service, message mail service.
Further, by the detailed entity relationship in six major class function modules and modules, the ontology taken out closes
System is as follows：
1) system includes function module；
2) platform management includes application management；Platform management includes management of process；
3) historical data base includes database table；
4) real-time data base includes real-time database table；
5) messaging bus includes message channel；Messaging bus includes message event；
6) service bus includes method of service；
7) public service includes rights service；Public service includes log services.
Further, the step of knowledge mapping of structure detailed service logic is as follows：
(1.1) ontology and ontological relationship are abstracted：According to the volume of the expertise of intelligent grid Dispatching Control System and program
Journey experience takes out the relationship between ontology and ontology from each component part of system；
(1.2) entity is captured：By the configuration file of system, real-time data base, historical data base, relative program source code with
And the Heuristics of expert obtains the entity information of intelligent grid Dispatching Control System professional knowledge；
(1.3) according to ontological relationship, entity relationship is established；
(1.4) cleaning and fusion of entity information：Firstly the need of the consistency for ensureing data, elimination is substantially same
Entity, but occur multiple situation due to different expression ways；When being extended entity attributes, need to judge
Whether the attribute overlaps with existing attribute, when being only a completely new attribute, just allows to add, to reduce the superfluous of data
Yu Xing.
Further, in step (1.2), application definition configuration file is parsed, the entity of acquisition includes：Real-time state is ground
Studying carefully state, planning state, test state, inverting state and training state, attribute includes：State number, state name；According to the information parsed, extraction
Ontology is " state "；
Parsing the definition about application, the entity being applied in this document includes：SCADA applications, PAS applications, DTS are answered
With, FES application, AGC applications, PUBLIC applications, WAMS applications, extraction ontology " application "；Under the file of storage dynamic base,
All entities about dynamic base are obtained, and summarize ontology " dynamic base ".
Further, real-time data base provides local IP access interface, the distant place service access interface of high speed；
The a large amount of historical data of historical data library storage；
All table information read from the table information table of real-time data base and historical data base respectively obtain real-time database table
With all entities of historical data base table the two ontologies, corresponding ontology is divided into other " real-time database table " and " historical data base
Table ".
Further, step (1.3) and include the following steps：
(1.3.1) parses the source code and configuration file of sca_analog process related services, obtains process and other entities
Between relationship；Entity relationship uses triplet format<Sca_analog, relationship A, entity 2>Indicate sca_analog and entity
There are relationship A between 2, and sca_analog and entity 2 are guest of honour's relationships, and position can not overturn；
(1.3.2) determines the specific example range of relationship A according to known ontological relationship；
(1.3.3) in engineering source code or makefile files, is obtained corresponding according to determining predicate and guest of honour's relationship
Entity 3, to set up complete entity relationship；
When (1.3.4) establishes entity relationship, for same type of entity relationship, answer front and back statement consistent, it otherwise can be by
It is considered a variety of different relationships, and causes data redundancy mistake；
For certain knowledge for being not easy to parse or can not parse, the function being manually entered is provided；Artificial addition ontology,
The correlation of entity and each entity, the convenient extension for knowledge.
Further, in step (2), the storage organization of knowledge mapping includes ontology definition table, entity table, ontological relationship
Table and entity relationship scheme；
The ontology definition table defines the database table name of all ontology informations and all kinds of entity informations of storage；
The entity table is to carry out classification storage according to ontology, and of a sort entity is stored in same table；
The ontological relationship table defines possessed relationship between different ontologies；
The entity relationship scheme defines the relationship between two entities；
The content of knowledge mapping uses triplet format<Entity 1, relationship, entity 2>It is stored, entity 1 and entity 2
Information storage is in entity table, and the details of relationship are stored in ontological relationship table, which avoids in every reality
The inconsistent mistake of data redundancy or data for all storing details in body relationship and occurring.
Further, in step (2), the displaying interface for safeguarding knowledge based collection of illustrative plates of knowledge mapping carries out, and is divided into
Four classes are safeguarded：Ontology configuration, ontological relationship configuration, entity configuration and entity relationship configuration.
Compared with prior art, beneficial effects of the present invention are：
The knowledge mapping that the present invention is built is presented abstract dispatch automated system professional knowledge in a manner of patterned
Out, user is allowed to be visually known the professional knowledge of whole system.User can operate corresponding entity simultaneously, select
Selecting property checks the professional knowledge that oneself is concerned about, has very strong interactivity and availability.
Service logic knowledge mapping provides following several functions：
1) process interdependent node is clicked, such as clicks sca_analog process icons, search should be into displaying automatically for system
The information such as message event, database table that journey uses；
2) real-time data base interdependent node is clicked, such as clicks telemeter node, system should by all readings or write-in
The process of table is shown.I.e. the knowledge mapping of service logic from different dimensions, can show that the business of automated system is closed
System.
If 3) user is not concerned with the business relations of some entity, the entity is clicked, the page automatically will therewith directly
Relevant knowledge mapping is deleted in the graphic.
4) drag operation can be carried out to the element in figure, and is preserved into template, convenient for use next time.
The knowledge mapping displaying of basic platform has following several features：
1) the whole structure composed of basic platform can be shown；
2) entity node in knowledge mapping has click function, and the industry of each function module can be checked after clicking to enter
Business logic.
3) entrance of detailed service logic knowledge mapping and the displaying shape of service logic knowledge mapping under each application are provided
It is integral.
Description of the drawings
Fig. 1 is basic platform knowledge mapping schematic diagram.
Fig. 2 is knowledge mapping storage organization figure.
Fig. 3 is basic platform knowledge mapping display diagram.
Fig. 4 is service logic knowledge mapping display diagram.
Specific implementation mode
With reference to the accompanying drawings and detailed description, detailed elaboration is made to specific embodiments of the present invention.These tools
Body embodiment is only not supposed to be a limitation to the present invention for narration or implementation principle, and protection scope of the present invention is still with power
Subject to profit requires, including obvious changes or variations etc. made on this basis.
1, the structure of knowledge mapping
Knowledge mapping is the semantic knowledge-base of structuring, for describing the concept in physical world and its phase with sign format
Mutual relation, the ontology of knowledge mapping is the concept artificially abstracted, and the object being truly present is entity.The structure of knowledge mapping
It builds and is generally divided into top-down and bottom-up two methods.Top-down construction method is that this is first taken out from data source
Body obtains term, the concept of top layer, synonymous and hierarchical relationship and relevant rule, then carries out the learning process of entity, will
Entity is concluded into the concept of front, is finally established the correlation between entity, is formed complete knowledge mapping.It is bottom-up
Construction method be first all entity and its association attributes are extracted from data source, the data of extraction are cleaned, then
The correlation between the entity of standardization is established, finally classifies to entity, is abstracted into ontology, and establish the pass between ontology
System, to form complete knowledge mapping.
Intelligent grid Dispatching Control System is that a typical dispatch automated system introduces knowledge herein for it
The structure of collection of illustrative plates.Intelligent grid Dispatching Control System is by the organization of unity of general headquarters of State Grid Corporation of China, concentrates research and development, will be original
More than 10 set independent utility systems inside one control centre, horizontal integrating is the electricity being made of basic platform and four major class applications
Net Dispatching Control System.
Use the bottom-up and top-down method being combined, structure intelligent grid Dispatching Control System basis flat herein
The knowledge mapping of platform and detailed service logic.Business relations in intelligent grid Dispatching Control System basic platform are relatively fixed,
Relationship between each entity is clear, needs to take out relationship between ontology from the relationship between each entity, thus
Knowledge mapping is built using bottom-up mode.The logic of detailed service is closed under each application of intelligent grid Dispatching Control System
System is complicated, and entity is more, needs first to take out the relationship between ontology, then constructs last business by the study of entity
Logical relation, therefore the knowledge mapping of detailed service logic is built using top-down mode.
1.1 structure basic platform knowledge mappings
Basic platform is the basis of intelligent grid Dispatching Control System, is responsible for the exploitation, operation and management of types of applications
General technical support is provided, is provided safeguard for the integrated and high efficient and reliable operation of whole system, including bus service, data are deposited
Storage service, public service and platform management etc..The knowledge mapping for building basic platform can clearly be shown each in basic platform
The detailed incidence relation of a module, to basic to provide a kind of detailed description using the personnel of intelligent grid Dispatching Control System
The methods of exhibiting of platform interior structure.
Include altogether six major class function modules in basic platform, is respectively：Platform management, historical data base, real-time data base,
Bus (messaging bus, service bus) and public service.
Platform management realizes the management to whole system by a set of management tool, including application management, management of process,
Clock management, log management and timing task management etc..Historical data base is mainly used to preserve grid equipment, parameter, history system
Meter information etc. all need the data of persistence.Real-time data base is used for providing efficient real time data access service.Bus
Service includes two kinds of messaging bus and service bus, provides reliable general information exchange mechanism and wide-area services mechanism, realizes
Safe and efficient data communication and application integration between control centre inside control centre.Public service be application exploitation and
It is integrated that one group of generic service, including graphical services, file service, rights service, message mail service etc. are provided.
By the detailed entity relationship in the six major class function module and modules, the ontological relationship taken out such as table 1
It is shown：
1 basic platform ontological relationship table of table
Using top-down method, in conjunction with the ontological relationship of basic platform, the basic platform detailed knowledge collection of illustrative plates of structure
Schematic diagram it is as shown in Figure 1.
1.2 structure service logic knowledge mappings
Service logic relationship under is that intelligent grid Dispatching Control System realizes that the function of dispatching of power netwoks control is realized,
The features such as, business relations various with type of business are complicated and business relations dynamic change.Build the knowledge graph of service logic
Spectrum, visualizes the call relation of complicated business, can be that the malfunction elimination of intelligent grid Dispatching Control System carries
Foundation for reference.
Build the knowledge mapping of service logic, it is necessary first to according to the expertise and journey of intelligent grid Dispatching Control System
The programming experience of sequence takes out the relationship between ontology and ontology from each component part of system, further according to the pass between ontology
Connection relationship carries out the detailed crawl of Business Entity, builds the relationship of entity, to form complete knowledge mapping.
1.2.1 ontology and ontological relationship are abstracted
According to the expertise of intelligent grid Dispatching Control System, part body and ontological relationship can be taken out, such as：
System includes state, and state includes application, using including process.According to the programming experience of computer major, can take out remaining
Ontology and ontological relationship, such as：Process calls dynamic base, process to send message etc..Relationship between detailed ontology and ontology,
As shown in the table：
2 detailed service logic ontological relationship table of table
| Ontology 1 | Relationship | Ontology 2 |
| Process | It uses | Configuration file |
| Process | It uses | Dynamic base |
| Process | Write-in | Real-time data base table |
| Process | It reads | Real-time data base table |
| Process | Write-in | Relation database table |
| Process | It reads | Relation database table |
| Process | It sends | Message event |
| Process | It receives | Message event |
| Process | Request | Service bus |
| Process | Response | Service bus |
| ... | ... | ... |
1.2.2 entity is captured
The entity information of intelligent grid Dispatching Control System professional knowledge can pass through the configuration file of system, in real time number
The acquisitions such as the Heuristics according to library, historical data base, relative program source code and expert.
(1) configuration file
In intelligent grid Dispatching Control System, configuration file, dynamic base, executable program etc. have specified file mesh
Record, in respective file directory, obtains all entity informations.Relevant configuration file is structuring or semi-structured mostly
, therefore content therein can be parsed according to the set form of configuration file.
Application definition configuration file is parsed, the entity of acquisition includes：Real-time state, research state, planning state, test state, inverting
State and training state, attribute include：State number, state name etc..According to the information parsed, extraction ontology is " state ".
Parsing the definition about application, the entity being applied in this document includes：SCADA applications, PAS applications, DTS are answered
With, FES application, AGC applications, PUBLIC applications, WAMS applications etc., extraction ontology " application ".In the file of storage dynamic base
Under, all entities about dynamic base are obtained, and summarize ontology " dynamic base ".
(2) real-time database and historical data base table
Real-time data base provides local IP access interface, the distant place service access interface of high speed, and historical data library storage is a large amount of
Historical data, two kinds of databases all have the characteristics that structuring, integrality and reliability.Table information table and domain information table are to adjust
Especially important two tables in automated system are spent, table information table defines the information of all tables in database, including table number, table
English name, table Chinese name, affiliated application, dominant record number etc., domain information table defines domain information all in every tables of data,
Including affiliated table, domain name, type, data length etc..The institute read from the table information table of real-time database and historical data base respectively
There is table information, obtain all entities of the two ontologies of real-time database table and historical data base table, corresponding ontology is divided into not " in real time
Library table " and " historical data base table ".
(3) bus
Messaging bus and service bus provide data interaction service for intelligent grid Dispatching Control System, realize same system
The transmission of data on interior difference node.Messaging bus classifies to message by event set, and event set is thing similar in function
The set of part.Parsing event set defines file, obtains all entities of event set, including PDR recording channels, event forwarding channel
Deng.Include different events in event set, distinguishes specific event using event number, by the configuration file of message event, obtain
All events entity, while extract ontology " messaging bus ", " message event collection " and " message event ".Service bus
The service of offer has real-time database service middata, historical data base service midhis, picture refreshing service midmmi, file clothes
Be engaged in ftpserv, event forwarding service evt_sender and evt_recv, Resource Location Services locator and remote access agency
Proxy is serviced, the entity and ontology of service bus are established.
(4) process
The related service of intelligent grid Dispatching Control System is run on computers in the form of process
, executable program is stored under bin catalogues, traversal this document folder, all information for executing programs of acquisition, including program name,
Size, renewal time etc. form specific entity such as：Fes_104, model_modify, msg_bus, rtdb_server etc.,
Corresponding ontology is " process ".
1.2.3 according to ontological relationship, entity relationship is established
The key for building intelligent grid Dispatching Control System professional knowledge collection of illustrative plates is the correlation established between process entity.
Sca_analog processes are the critical processes of SCADA applications, are built to the entity relationship of sca_analog processes, Neng Gouti
Whole features of service logic knowledge mapping are now built, detailed construction step is as follows：
1) source code and configuration file for parsing sca_analog process related services, obtain between process and other entities
Relationship.Entity relationship uses triplet format<Sca_analog, relationship A, entity 2>It indicates between sca_analog and entity 2
There are relationship A, and sca_analog and entity 2 are guest of honour's relationships, and position can not overturn.
2) according to known ontological relationship, the specific example range of relationship A is determined, such as：Entity 1 be sca_analog into
Journey, then it was determined that relationship A is：It calls, send, receive, read, and write-in etc.；
3) corresponding entity is obtained in engineering source code or makefile files according to determining predicate and guest of honour's relationship
3, to set up complete entity relationship, such as<Sca_analog processes are called, the libraries Librte.so>、<sca_analog
Process is read, full telemeter>、<Sca_analog processes receive, full telemetry event>.
4) it when establishing entity relationship, for same type of entity relationship, answers front and back statement consistent, otherwise can be considered as
A variety of different relationships, and cause data redundancy mistake.For certain knowledge for being not easy to parse or can not parse, hand is provided
The function of dynamic typing.The correlation of ontology, entity and each entity, the convenient extension for knowledge can manually be added.
1.2.4 the cleaning and fusion of entity information
When being constantly filled the relationship between entity to entity and being extended, needs to carry out the cleaning of data and melt
It closes.Firstly the need of the consistency for ensureing data, elimination is substantially the same entity, but is gone out due to different expression ways
Now multiple situation.When being extended entity attributes, need to judge whether the attribute overlaps with existing attribute, only
When being a completely new attribute, just allow to add, to reduce the redundancy of data.
2, the storage and maintenance of knowledge
The storage organization of knowledge mapping as shown in Fig. 2, according to the content in ontology definition table, can example dissolve a variety of realities
Body surface；Then it is based on ontological relationship table, the multiple entity tables dissolved in conjunction with example again, so that it may to construct entity relationship scheme, from
And complete knowledge mapping can be stored.
Ontology definition table：Define the database table name of all ontology informations and all kinds of entity informations of storage；
Entity table：Entity table is to carry out classification storage according to ontology, and of a sort entity is stored in same table；
Ontological relationship table：Possessed relationship between different ontologies is defined, such as：Between " application " and " process "
"comprising" relationship, " transmission data " between " process " and " message event " and " receiving data " relationship are also stored in the table
The information such as the Chinese and English description of ontological relationship.
Entity relationship scheme：Define the relationship between two entities.The content of knowledge mapping uses triplet format<Entity 1,
Relationship, entity 2>It is stored, for the information storage of entity 1 and entity 2 in entity table, the details of relationship are stored in ontology
In relation table, which avoids the data redundancy or number for all storing details in every entity relationship and occurring
According to inconsistent mistake.
The storage organization clearly shown all ontology informations and its between relationship, all kinds of entities divide by type
Table stores, convenient for the maintenance to all kinds of entities.Relationship of the ontological relationship table between entity is constrained, and same-type is avoided
Relationship there is different statements, and the problem of be mistakened as into a variety of relationships.
Meanwhile the storage organization is convenient for the extension of knowledge mapping information, if finding new knowledge, it is only necessary in this body surface
Corresponding record is added, establishes corresponding entity table, and establish entity relationship, the model framework of whole system need not change
Become.
3, the displaying and application of knowledge mapping
The knowledge mapping content of entire intelligent grid Dispatching Control System is more, and relationship is complicated, therefore front page layout
The basic platform of system and detailed professional knowledge collection of illustrative plates are illustrated, each entity node of knowledge mapping of basic platform is relatively solid
It is fixed, it is capable of providing the general frame knowledge of intelligent grid Dispatching Control System, the knowledge mapping content of service logic is more, relationship
Complexity is capable of providing the detailed logic relationship of intelligent grid Dispatching Control System.
3.1 basic platform knowledge mappings are shown
As shown in figure 3, the knowledge mapping displaying of basic platform has following several features：
1) the whole structure composed of basic platform can be shown；
2) entity node in knowledge mapping has click function, and the industry of each function module can be checked after clicking to enter
Business logic.
3) entrance of detailed service logic knowledge mapping and the displaying shape of service logic knowledge mapping under each application are provided
It is integral.
3.2 service logic knowledge mappings are shown
As shown in figure 4, service logic knowledge mapping relationship is complex, there are complicated predicates between each entity
Relationship.In conjunction with appeal feature, service logic knowledge mapping provides following several functions：
1) process interdependent node is clicked, such as clicks sca_analog process icons, search should be into displaying automatically for system
The information such as message event, database table that journey uses；
2) real-time data base interdependent node is clicked, such as clicks telemeter node, system should by all readings or write-in
The process of table is shown.I.e. the knowledge mapping of service logic from different dimensions, can show that the business of automated system is closed
System.
If 3) user is not concerned with the business relations of some entity, the entity is clicked, the page automatically will therewith directly
Relevant knowledge mapping is deleted in the graphic.
4) drag operation can be carried out to the element in figure, and is preserved into template, convenient for use next time.
Knowledge mapping will be abstract dispatch automated system professional knowledge, showed in a manner of patterned, allow use
Person is visually known the professional knowledge of whole system.User can operate corresponding entity simultaneously, selectively check certainly
The professional knowledge that oneself is concerned about has very strong interactivity and availability.
Claims (9)
1. a kind of structure and application process of dispatch automated system knowledge mapping, it is characterised in that：
It the described method comprises the following steps：
(1) structure of knowledge mapping：The basic platform of intelligent grid Dispatching Control System is built using bottom-up mode
Knowledge mapping builds the knowledge mapping of the detailed service logic of intelligent grid Dispatching Control System using top-down mode；
(2) storage and maintenance of knowledge mapping：The data of knowledge mapping are stored based on historical data base, the dimension of knowledge mapping
The displaying interface for protecting knowledge based collection of illustrative plates carries out；
(3) displaying and application of knowledge mapping：The basic platform of front page layout display systems and detailed professional knowledge collection of illustrative plates, base
The general frame knowledge of the knowledge mapping displaying intelligent grid Dispatching Control System of plinth platform, the knowledge mapping displaying of service logic
The detailed logic relationship of intelligent grid Dispatching Control System.
2. the structure and application process of a kind of dispatch automated system knowledge mapping according to claim 1, feature exist
In：
In step (1), includes altogether six major class function modules in the basic platform, be respectively：Platform management, historical data
Library, real-time data base, messaging bus, service bus and public service；
The platform management realizes the management to whole system by a set of management tool, including application management, management of process,
Clock management, log management and timing task management；
The historical data base is mainly used to preserve grid equipment, parameter, historical statistical information；
The real-time data base is used for providing efficient real time data access service；
The messaging bus and service bus are used to provide reliable general information exchange mechanism and wide-area services mechanism, realize and adjust
Spend safe and efficient data communication and application integration between central interior and control centre；
The public service is the exploitation of application and integrated provides one group of generic service, including graphical services, file service, permission
Service, message mail service.
3. the structure and application process of a kind of dispatch automated system knowledge mapping according to claim 2, feature exist
In：
By the detailed entity relationship in six major class function modules and modules, the ontological relationship taken out is as follows：
1) system includes function module；
2) platform management includes application management；Platform management includes management of process；
3) historical data base includes database table；
4) real-time data base includes real-time database table；
5) messaging bus includes message channel；Messaging bus includes message event；
6) service bus includes method of service；
7) public service includes rights service；Public service includes log services.
4. the structure and application process of a kind of dispatch automated system knowledge mapping according to claim 1, feature exist
In：
The step of building the knowledge mapping of detailed service logic is as follows：
(1.1) ontology and ontological relationship are abstracted：It is passed through according to the programming of the expertise of intelligent grid Dispatching Control System and program
Test the relationship taken out from each component part of system between ontology and ontology；
(1.2) entity is captured：By the configuration file of system, real-time data base, historical data base, relative program source code and specially
The Heuristics of family obtains the entity information of intelligent grid Dispatching Control System professional knowledge；
(1.3) according to ontological relationship, entity relationship is established；
(1.4) cleaning and fusion of entity information：Firstly the need of the consistency for ensureing data, elimination is substantially the same reality
Body, but occur multiple situation due to different expression ways；When being extended entity attributes, need to judge to be somebody's turn to do
Whether attribute overlaps with existing attribute, when being only a completely new attribute, just allows to add, to reduce the redundancy of data
Property.
5. the structure and application process of a kind of dispatch automated system knowledge mapping according to claim 4, feature exist
In：
In step (1.2), application definition configuration file is parsed, the entity of acquisition includes：Real-time state, planning state, is surveyed research state
Trying state, inverting state and training state, attribute includes：State number, state name；According to the information parsed, extraction ontology is " state "；
Parsing the definition about application, the entity being applied in this document includes：SCADA applications, PAS are applied, DTS is applied,
FES applications, AGC applications, PUBLIC applications, WAMS applications, extraction ontology " application "；Under the file of storage dynamic base, obtain
All entities about dynamic base are obtained, and summarize ontology " dynamic base ".
6. the structure and application process of a kind of dispatch automated system knowledge mapping according to claim 4, feature exist
In：
Real-time data base provides local IP access interface, the distant place service access interface of high speed；
The a large amount of historical data of historical data library storage；
All table information read from the table information table of real-time data base and historical data base respectively obtain real-time database table and go through
All entities of the two ontologies of history database table, corresponding ontology are divided into other " real-time database table " and " historical data base table ".
7. the structure and application process of a kind of dispatch automated system knowledge mapping according to claim 4, feature exist
In：
Step (1.3) and include the following steps：
(1.3.1) parses the source code and configuration file of sca_analog process related services, obtains between process and other entities
Relationship；Entity relationship uses triplet format<Sca_analog, relationship A, entity 2>Indicate sca_analog and entity 2 it
Between there are relationship A, and sca_analog and entity 2 are guest of honour's relationships, and position can not overturn；
(1.3.2) determines the specific example range of relationship A according to known ontological relationship；
(1.3.3) obtains corresponding entity according to determining predicate and guest of honour's relationship in engineering source code or makefile files
3, to set up complete entity relationship；
When (1.3.4) establishes entity relationship, for same type of entity relationship, answers front and back statement consistent, otherwise can be considered
It is a variety of different relationships, and causes data redundancy mistake；
For certain knowledge for being not easy to parse or can not parse, the function being manually entered is provided；Artificial addition ontology, entity
And the correlation of each entity, the convenient extension for knowledge.
8. the structure and application process of a kind of dispatch automated system knowledge mapping according to claim 1, feature exist
In：
In step (2), the storage organization of knowledge mapping includes ontology definition table, entity table, ontological relationship table and entity relationship
Table；
The ontology definition table defines the database table name of all ontology informations and all kinds of entity informations of storage；
The entity table is to carry out classification storage according to ontology, and of a sort entity is stored in same table；
The ontological relationship table defines possessed relationship between different ontologies；
The entity relationship scheme defines the relationship between two entities；
The content of knowledge mapping uses triplet format<Entity 1, relationship, entity 2>It is stored, the information of entity 1 and entity 2
It is stored in entity table, the details of relationship are stored in ontological relationship table, which avoids closes in every entity
The inconsistent mistake of data redundancy or data for all storing details in system and occurring.
9. the structure and application process of a kind of dispatch automated system knowledge mapping according to claim 1, feature exist
In：
In step (2), the displaying interface for safeguarding knowledge based collection of illustrative plates of knowledge mapping carries out, and is divided into the maintenance of four classes：Ontology
Configuration, ontological relationship configuration, entity configuration and entity relationship configuration.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711180687.1A CN108595449A (en) | 2017-11-23 | 2017-11-23 | The structure and application process of dispatch automated system knowledge mapping |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711180687.1A CN108595449A (en) | 2017-11-23 | 2017-11-23 | The structure and application process of dispatch automated system knowledge mapping |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108595449A true CN108595449A (en) | 2018-09-28 |
Family
ID=63633065
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711180687.1A Pending CN108595449A (en) | 2017-11-23 | 2017-11-23 | The structure and application process of dispatch automated system knowledge mapping |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108595449A (en) |
Cited By (36)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109446343A (en) * | 2018-11-05 | 2019-03-08 | 上海德拓信息技术股份有限公司 | A kind of method of public safety knowledge mapping building |
| CN109471949A (en) * | 2018-11-09 | 2019-03-15 | 袁琦 | A kind of semi-automatic construction method of pet knowledge mapping |
| CN109739993A (en) * | 2018-12-06 | 2019-05-10 | 深圳云天励飞技术有限公司 | Dress ornament knowledge mapping display methods, device, figure server and storage medium |
| CN109885692A (en) * | 2019-01-11 | 2019-06-14 | 平安科技（深圳）有限公司 | Knowledge data storage method, device, computer equipment and storage medium |
| CN109933673A (en) * | 2019-02-18 | 2019-06-25 | 北京明略软件系统有限公司 | A kind of relation map generation method and device |
| CN110008288A (en) * | 2019-02-19 | 2019-07-12 | 武汉烽火技术服务有限公司 | The construction method in the knowledge mapping library for Analysis of Network Malfunction and its application |
| CN110399497A (en) * | 2019-07-02 | 2019-11-01 | 厦门美域中央信息科技有限公司 | A kind of adaptive construction method of knowledge mapping based on depth learning technology |
| CN110399512A (en) * | 2019-07-25 | 2019-11-01 | 北京明略软件系统有限公司 | A kind of map memory management method and device |
| CN110750600A (en) * | 2019-10-15 | 2020-02-04 | 北京明略软件系统有限公司 | Information processing method and device |
| CN110825885A (en) * | 2019-11-13 | 2020-02-21 | 南方电网科学研究院有限责任公司 | Power equipment knowledge graph application system |
| CN110955782A (en) * | 2019-11-15 | 2020-04-03 | 国网甘肃省电力公司 | Scheduling control knowledge representation method based on knowledge graph |
| CN110990582A (en) * | 2019-11-21 | 2020-04-10 | 北京明略软件系统有限公司 | Method, device, computer storage medium and terminal for realizing transaction processing |
| CN110992002A (en) * | 2019-12-05 | 2020-04-10 | 腾讯云计算（北京）有限责任公司 | Item processing method, item processing device, item processing equipment and storage medium |
| CN111080263A (en) * | 2019-12-20 | 2020-04-28 | 南京烽火星空通信发展有限公司 | Visual collaborative analysis system based on thought-guide graph |
| CN111143448A (en) * | 2019-12-03 | 2020-05-12 | 北京博瑞彤芸科技股份有限公司 | Knowledge base construction method |
| CN111177400A (en) * | 2019-12-05 | 2020-05-19 | 国网能源研究院有限公司 | Associated display method and device of equipment, service and data based on knowledge graph |
| CN111223004A (en) * | 2019-11-14 | 2020-06-02 | 国网湖北省电力有限公司电力科学研究院 | Relay protection knowledge modeling method and platform for business application |
| CN111291194A (en) * | 2020-01-20 | 2020-06-16 | 深圳供电局有限公司 | Automatic storage and knowledge graph generation method and device |
| CN111474444A (en) * | 2020-04-14 | 2020-07-31 | 国网山东省电力公司电力科学研究院 | Line fault power restoration decision method based on knowledge graph |
| CN111552820A (en) * | 2020-04-30 | 2020-08-18 | 江河瑞通（北京）技术有限公司 | Water engineering scheduling data processing method and device |
| CN111563170A (en) * | 2020-04-30 | 2020-08-21 | 北京明略软件系统有限公司 | Knowledge graph generation method and device, computer storage medium and terminal |
| CN111768077A (en) * | 2020-05-28 | 2020-10-13 | 国网浙江省电力有限公司绍兴供电公司 | Intelligent power grid trip event identification method based on knowledge graph |
| CN111897971A (en) * | 2020-07-29 | 2020-11-06 | 中国电力科学研究院有限公司 | Knowledge graph management method and system suitable for field of power grid dispatching control |
| WO2020228416A1 (en) * | 2019-05-14 | 2020-11-19 | 京东数字科技控股有限公司 | Responding method and device |
| CN112256884A (en) * | 2020-10-23 | 2021-01-22 | 国网辽宁省电力有限公司信息通信分公司 | Knowledge graph-based data asset library access method and device |
| CN112418735A (en) * | 2020-12-15 | 2021-02-26 | 深圳供电局有限公司 | Power grid AI scheduling system and method based on graph calculation |
| CN112463980A (en) * | 2020-11-25 | 2021-03-09 | 南京摄星智能科技有限公司 | Intelligent plan recommendation method based on knowledge graph |
| CN112487789A (en) * | 2020-11-27 | 2021-03-12 | 贵州电网有限责任公司 | Operation order scheduling logic validity verification method based on knowledge graph |
| CN112699252A (en) * | 2021-03-25 | 2021-04-23 | 成都数联铭品科技有限公司 | Processing method of attribute data applied to knowledge graph and electronic equipment |
| CN112948638A (en) * | 2019-12-11 | 2021-06-11 | 中国移动通信集团海南有限公司 | Map construction method and device, storage medium and computer equipment |
| CN112948572A (en) * | 2019-12-11 | 2021-06-11 | 中国科学院沈阳计算技术研究所有限公司 | Method for visually displaying equipment information and relation of power system through knowledge graph |
| CN113326345A (en) * | 2020-02-28 | 2021-08-31 | 拓尔思天行网安信息技术有限责任公司 | Knowledge graph analysis and application method, platform and equipment based on dynamic ontology |
| CN113609257A (en) * | 2021-08-09 | 2021-11-05 | 神州数码融信软件有限公司 | Financial knowledge map elastic framework construction method |
| WO2022001924A1 (en) * | 2020-06-30 | 2022-01-06 | 华为技术有限公司 | Knowledge graph construction method, apparatus and system and computer storage medium |
| WO2022061925A1 (en) * | 2020-09-28 | 2022-03-31 | 西门子股份公司 | Method and apparatus for generating control chart of automatic control system, and computer readable medium |
| CN115391545A (en) * | 2022-04-26 | 2022-11-25 | 航天宏图信息技术股份有限公司 | Knowledge graph construction method and device for multi-platform collaborative observation task |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105183869A (en) * | 2015-09-16 | 2015-12-23 | 分众(中国)信息技术有限公司 | Building knowledge mapping database and construction method thereof |
| US20160379120A1 (en) * | 2015-06-25 | 2016-12-29 | International Business Machines Corporation | Knowledge Canvassing Using a Knowledge Graph and a Question and Answer System |
| CN106447346A (en) * | 2016-08-29 | 2017-02-22 | 北京中电普华信息技术有限公司 | Method and system for construction of intelligent electric power customer service system |
| CN106874378A (en) * | 2017-01-05 | 2017-06-20 | 北京工商大学 | The entity of rule-based model extracts the method that knowledge mapping is built with relation excavation |
| CN107301235A (en) * | 2017-06-27 | 2017-10-27 | 山东浪潮商用系统有限公司 | A kind of communicating knowledge collection of illustrative plates display systems |
| CN107330125A (en) * | 2017-07-20 | 2017-11-07 | 云南电网有限责任公司电力科学研究院 | The unstructured distribution data integrated approach of magnanimity of knowledge based graphical spectrum technology |
-
2017
- 2017-11-23 CN CN201711180687.1A patent/CN108595449A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160379120A1 (en) * | 2015-06-25 | 2016-12-29 | International Business Machines Corporation | Knowledge Canvassing Using a Knowledge Graph and a Question and Answer System |
| CN105183869A (en) * | 2015-09-16 | 2015-12-23 | 分众(中国)信息技术有限公司 | Building knowledge mapping database and construction method thereof |
| CN106447346A (en) * | 2016-08-29 | 2017-02-22 | 北京中电普华信息技术有限公司 | Method and system for construction of intelligent electric power customer service system |
| CN106874378A (en) * | 2017-01-05 | 2017-06-20 | 北京工商大学 | The entity of rule-based model extracts the method that knowledge mapping is built with relation excavation |
| CN107301235A (en) * | 2017-06-27 | 2017-10-27 | 山东浪潮商用系统有限公司 | A kind of communicating knowledge collection of illustrative plates display systems |
| CN107330125A (en) * | 2017-07-20 | 2017-11-07 | 云南电网有限责任公司电力科学研究院 | The unstructured distribution data integrated approach of magnanimity of knowledge based graphical spectrum technology |
Non-Patent Citations (2)
| Title |
|---|
| 宁剑: ""智能电网调度控制系统基础平台公共服务技术规范解读"", 《智能电网》, vol. 5, no. 3, pages 314 - 318 * |
| 李涛等: ""知识图谱的发展与构建"", 《南京理工大学学报》, vol. 41, no. 1, pages 22 - 33 * |
Cited By (52)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109446343A (en) * | 2018-11-05 | 2019-03-08 | 上海德拓信息技术股份有限公司 | A kind of method of public safety knowledge mapping building |
| CN109446343B (en) * | 2018-11-05 | 2020-10-27 | 上海德拓信息技术股份有限公司 | Public safety knowledge graph construction method |
| CN109471949A (en) * | 2018-11-09 | 2019-03-15 | 袁琦 | A kind of semi-automatic construction method of pet knowledge mapping |
| CN109739993A (en) * | 2018-12-06 | 2019-05-10 | 深圳云天励飞技术有限公司 | Dress ornament knowledge mapping display methods, device, figure server and storage medium |
| CN109885692B (en) * | 2019-01-11 | 2023-06-16 | 平安科技（深圳）有限公司 | Knowledge data storage method, apparatus, computer device and storage medium |
| CN109885692A (en) * | 2019-01-11 | 2019-06-14 | 平安科技（深圳）有限公司 | Knowledge data storage method, device, computer equipment and storage medium |
| CN109933673A (en) * | 2019-02-18 | 2019-06-25 | 北京明略软件系统有限公司 | A kind of relation map generation method and device |
| CN110008288A (en) * | 2019-02-19 | 2019-07-12 | 武汉烽火技术服务有限公司 | The construction method in the knowledge mapping library for Analysis of Network Malfunction and its application |
| CN110008288B (en) * | 2019-02-19 | 2021-06-29 | 武汉烽火技术服务有限公司 | Construction method and application of knowledge map library for network fault analysis |
| WO2020228416A1 (en) * | 2019-05-14 | 2020-11-19 | 京东数字科技控股有限公司 | Responding method and device |
| CN110399497A (en) * | 2019-07-02 | 2019-11-01 | 厦门美域中央信息科技有限公司 | A kind of adaptive construction method of knowledge mapping based on depth learning technology |
| CN110399512A (en) * | 2019-07-25 | 2019-11-01 | 北京明略软件系统有限公司 | A kind of map memory management method and device |
| CN110750600A (en) * | 2019-10-15 | 2020-02-04 | 北京明略软件系统有限公司 | Information processing method and device |
| CN110825885B (en) * | 2019-11-13 | 2022-06-17 | 南方电网科学研究院有限责任公司 | Power equipment knowledge graph application system |
| CN110825885A (en) * | 2019-11-13 | 2020-02-21 | 南方电网科学研究院有限责任公司 | Power equipment knowledge graph application system |
| CN111223004A (en) * | 2019-11-14 | 2020-06-02 | 国网湖北省电力有限公司电力科学研究院 | Relay protection knowledge modeling method and platform for business application |
| CN110955782A (en) * | 2019-11-15 | 2020-04-03 | 国网甘肃省电力公司 | Scheduling control knowledge representation method based on knowledge graph |
| CN110955782B (en) * | 2019-11-15 | 2023-07-07 | 国网甘肃省电力公司 | Knowledge graph-based scheduling control knowledge representation method |
| CN110990582A (en) * | 2019-11-21 | 2020-04-10 | 北京明略软件系统有限公司 | Method, device, computer storage medium and terminal for realizing transaction processing |
| CN111143448A (en) * | 2019-12-03 | 2020-05-12 | 北京博瑞彤芸科技股份有限公司 | Knowledge base construction method |
| CN111143448B (en) * | 2019-12-03 | 2023-05-12 | 北京博瑞彤芸科技股份有限公司 | Knowledge base construction method |
| CN110992002B (en) * | 2019-12-05 | 2023-04-18 | 腾讯云计算（北京）有限责任公司 | Item processing method, item processing device, item processing equipment and storage medium |
| CN110992002A (en) * | 2019-12-05 | 2020-04-10 | 腾讯云计算（北京）有限责任公司 | Item processing method, item processing device, item processing equipment and storage medium |
| CN111177400B (en) * | 2019-12-05 | 2023-07-25 | 国网能源研究院有限公司 | Knowledge graph-based equipment, business and data associated display method and device |
| CN111177400A (en) * | 2019-12-05 | 2020-05-19 | 国网能源研究院有限公司 | Associated display method and device of equipment, service and data based on knowledge graph |
| CN112948638B (en) * | 2019-12-11 | 2023-09-05 | 中国移动通信集团海南有限公司 | Map construction method, device, storage medium and computer equipment |
| CN112948638A (en) * | 2019-12-11 | 2021-06-11 | 中国移动通信集团海南有限公司 | Map construction method and device, storage medium and computer equipment |
| CN112948572A (en) * | 2019-12-11 | 2021-06-11 | 中国科学院沈阳计算技术研究所有限公司 | Method for visually displaying equipment information and relation of power system through knowledge graph |
| CN111080263A (en) * | 2019-12-20 | 2020-04-28 | 南京烽火星空通信发展有限公司 | Visual collaborative analysis system based on thought-guide graph |
| CN111080263B (en) * | 2019-12-20 | 2021-07-23 | 南京烽火星空通信发展有限公司 | Visual collaborative analysis system based on thought-guide graph |
| CN111291194A (en) * | 2020-01-20 | 2020-06-16 | 深圳供电局有限公司 | Automatic storage and knowledge graph generation method and device |
| CN113326345A (en) * | 2020-02-28 | 2021-08-31 | 拓尔思天行网安信息技术有限责任公司 | Knowledge graph analysis and application method, platform and equipment based on dynamic ontology |
| CN111474444B (en) * | 2020-04-14 | 2022-06-21 | 国网山东省电力公司电力科学研究院 | Line fault power restoration decision method based on knowledge graph |
| CN111474444A (en) * | 2020-04-14 | 2020-07-31 | 国网山东省电力公司电力科学研究院 | Line fault power restoration decision method based on knowledge graph |
| CN111552820A (en) * | 2020-04-30 | 2020-08-18 | 江河瑞通（北京）技术有限公司 | Water engineering scheduling data processing method and device |
| CN111563170A (en) * | 2020-04-30 | 2020-08-21 | 北京明略软件系统有限公司 | Knowledge graph generation method and device, computer storage medium and terminal |
| CN111768077A (en) * | 2020-05-28 | 2020-10-13 | 国网浙江省电力有限公司绍兴供电公司 | Intelligent power grid trip event identification method based on knowledge graph |
| CN111768077B (en) * | 2020-05-28 | 2023-12-01 | 国网浙江省电力有限公司绍兴供电公司 | Intelligent identification method for power grid tripping event based on knowledge graph |
| WO2022001924A1 (en) * | 2020-06-30 | 2022-01-06 | 华为技术有限公司 | Knowledge graph construction method, apparatus and system and computer storage medium |
| CN111897971B (en) * | 2020-07-29 | 2023-04-07 | 中国电力科学研究院有限公司 | Knowledge graph management method and system suitable for field of power grid dispatching control |
| CN111897971A (en) * | 2020-07-29 | 2020-11-06 | 中国电力科学研究院有限公司 | Knowledge graph management method and system suitable for field of power grid dispatching control |
| WO2022061925A1 (en) * | 2020-09-28 | 2022-03-31 | 西门子股份公司 | Method and apparatus for generating control chart of automatic control system, and computer readable medium |
| CN112256884A (en) * | 2020-10-23 | 2021-01-22 | 国网辽宁省电力有限公司信息通信分公司 | Knowledge graph-based data asset library access method and device |
| CN112463980A (en) * | 2020-11-25 | 2021-03-09 | 南京摄星智能科技有限公司 | Intelligent plan recommendation method based on knowledge graph |
| CN112487789B (en) * | 2020-11-27 | 2023-12-01 | 贵州电网有限责任公司 | Operation ticket scheduling logic validity verification method based on knowledge graph |
| CN112487789A (en) * | 2020-11-27 | 2021-03-12 | 贵州电网有限责任公司 | Operation order scheduling logic validity verification method based on knowledge graph |
| CN112418735A (en) * | 2020-12-15 | 2021-02-26 | 深圳供电局有限公司 | Power grid AI scheduling system and method based on graph calculation |
| CN112699252A (en) * | 2021-03-25 | 2021-04-23 | 成都数联铭品科技有限公司 | Processing method of attribute data applied to knowledge graph and electronic equipment |
| CN113609257A (en) * | 2021-08-09 | 2021-11-05 | 神州数码融信软件有限公司 | Financial knowledge map elastic framework construction method |
| CN113609257B (en) * | 2021-08-09 | 2024-03-22 | 神州数码融信软件有限公司 | Financial knowledge graph elastic framework construction method |
| CN115391545A (en) * | 2022-04-26 | 2022-11-25 | 航天宏图信息技术股份有限公司 | Knowledge graph construction method and device for multi-platform collaborative observation task |
| CN115391545B (en) * | 2022-04-26 | 2024-06-28 | 航天宏图信息技术股份有限公司 | Knowledge graph construction method and device for multi-platform collaborative observation task |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108595449A (en) | The structure and application process of dispatch automated system knowledge mapping | |
| Zhu et al. | Intelligent learning for knowledge graph towards geological data | |
| CN103631882B (en) | Semantization service generation system and method based on graph mining technique | |
| CN101799835B (en) | Ontology-driven geographic information retrieval system and method | |
| Hor et al. | A semantic graph database for BIM-GIS integrated information model for an intelligent urban mobility web application | |
| CN109284394A (en) | A method of Company Knowledge map is constructed from multi-source data integration visual angle | |
| CN103793372A (en) | Extracting semantic relationships from table structures in electronic documents | |
| McGlinn et al. | Publishing authoritative geospatial data to support interlinking of building information models | |
| CN106294520A (en) | The information extracted from document is used to carry out identified relationships | |
| US10776351B2 (en) | Automatic core data service view generator | |
| BRPI1105271A2 (en) | Method, and one or more computer readable media. | |
| Yuan et al. | Research on the standardization model of data semantics in the knowledge graph construction of Oil&Gas industry | |
| An et al. | Synapse: Towards linked data for smart cities using a semantic annotation framework | |
| Li et al. | Spatio-temporal data fusion techniques for modeling digital twin City | |
| Ronzhin | Semantic enrichment of Volunteered Geographic Information using Linked Data: a use case scenario for disaster management | |
| Jian et al. | A multi-agent based knowledge search framework to support the product development process | |
| Zhang et al. | Semantic web and geospatial unique features based geospatial data integration | |
| Seok et al. | Implementing A Semantic-based loT Mashup Service | |
| Plewe | A qualified assertion database for the history of places | |
| Yu et al. | A linked data approach for information integration between BIM and sensor data | |
| Rafatirad et al. | Contextual augmentation of ontology for recognizing sub-events | |
| Șimonca et al. | Analytical Capabilities of Graphs in Oracle Multimodel Database | |
| Ruoxin et al. | Design of MICE service platform based on big data | |
| Pashazadeh et al. | Modeling Chandy–Lamport Distributed Snapshot Algorithm Using Colored Petri Net | |
| Zhang et al. | Semantic-Based geospatial data integration with unique |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20180928 |