Huang et al., 2022 - Google Patents
A novel approach to predict network reliability for multistate networks by a deep neural networkHuang et al., 2022
- Document ID
- 10855394948819106451
- Author
- Huang C
- Huang D
- Lin Y
- Publication year
- Publication venue
- Quality Technology & Quantitative Management
External Links
Snippet
Real-world systems, such as manufacturing or computer systems, can be modeled as multistate network (MSN) consisting of arcs with stochastic capacity. Network reliability for an MSN is described as the probability that the system can meet the demand. The network …
- 230000001537 neural 0 title abstract description 51
Classifications
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- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
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- G—PHYSICS
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- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
- G06Q10/063—Operations research or analysis
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- G06Q50/00—Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
- G06Q50/01—Social networking
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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