CN116050773A - Industry fusion method and system based on carbon emission evaluation - Google Patents
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Abstract
The invention discloses an industry fusion method and system based on carbon emission evaluation, belonging to the technical field of data processing, wherein the method comprises the following steps: a carbon emission evaluation model is constructed by obtaining a carbon emission amount set, a carbon emission intensity set, and an emission change rate set. And inputting the carbon emission data obtained by the carbon into a carbon emission evaluation model to obtain an evaluation result set and a comprehensive evaluation result. And respectively inputting the evaluation results of each enterprise in the evaluation result set and the comprehensive evaluation result set into a carbon emission reduction analysis model to obtain carbon emission reduction measures. And then clustering enterprises to obtain an industry clustering result and an industry carbon emission reduction measure set. And according to the size of the enterprise scale, weighting calculation is carried out on measure parameters in the carbon emission reduction measure sets of the industries, so that carbon emission reduction fusion measures of the industries are obtained, and carbon emission reduction is carried out. The technical problems of low evaluation efficiency and inaccurate acquisition of carbon emission reduction measures in different industries in the prior art are solved.
Description
Technical field:
the invention relates to the field of data processing, in particular to an industry fusion method and system based on carbon emission evaluation.
The background technology is as follows:
the carbon emission is greenhouse gas emission generated in the production process of enterprises, and the evaluation of the carbon emission has important guiding significance for preparing carbon emission reduction measures. In the prior art, the evaluation of the carbon emission of different industries in a certain area is a complex work, a large amount of data acquisition and processing are needed to be manually performed, so that the evaluation efficiency of the carbon emission of different industries in the area is low, the carbon emission reduction measures manufactured in different industries cannot be accurately acquired, the execution and management difficulties of the carbon emission reduction measures in different industries are high, and the execution effect is poor.
Therefore, in the prior art, the evaluation efficiency is low, and the technical problem of inaccurate acquisition of carbon emission reduction measures in different industries exists.
The invention comprises the following steps:
the industrial fusion method and system based on carbon emission evaluation solve the technical problems that in the prior art, the evaluation efficiency is low, and carbon emission reduction measures in different industries are obtained inaccurately.
The application provides an industry fusion method based on carbon emission assessment, which comprises the steps of obtaining carbon emission, carbon emission intensity and emission change rate of a plurality of enterprises in a target area in a preset time period, and obtaining a carbon emission set, a carbon emission intensity set and an emission change rate set; constructing a carbon emission evaluation model, wherein the carbon emission evaluation model comprises a first evaluation unit, a second evaluation unit, a third evaluation unit and a comprehensive evaluation unit; inputting the data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set into the first evaluation unit, the second evaluation unit and the third evaluation unit respectively, and merging and inputting the data into the comprehensive evaluation unit to obtain a first evaluation result set, a second evaluation result set, a third evaluation result set and a comprehensive evaluation result set; inputting the evaluation results of each enterprise in the first evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set into a carbon emission reduction analysis model to obtain a carbon emission reduction measure set, wherein the carbon emission reduction measure of each enterprise comprises a plurality of measure parameters; clustering the enterprises according to a plurality of industries to obtain a plurality of industry clustering results and a plurality of industry carbon emission reduction measure sets; and weighting calculation is carried out on measure parameters in the industry carbon emission reduction measure sets according to the enterprise scale in the industry clustering results to obtain industry carbon emission reduction fusion measures, and carbon emission reduction is carried out.
The application also provides an industry fusion system based on carbon emission evaluation, wherein the emission data acquisition module is used for acquiring carbon emission, carbon emission intensity and emission change rate of a plurality of enterprises in a target area in a preset time period and acquiring a carbon emission set, a carbon emission intensity set and an emission change rate set; the carbon emission evaluation model construction module is used for constructing a carbon emission evaluation model, wherein the carbon emission evaluation model comprises a first evaluation unit, a second evaluation unit, a third evaluation unit and a comprehensive evaluation unit; the evaluation result acquisition module is used for respectively inputting the data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set into the first evaluation unit, the second evaluation unit and the third evaluation unit, and merging and inputting the data into the comprehensive evaluation unit to obtain a first evaluation result set, a second evaluation result set, a third evaluation result set and a comprehensive evaluation result set; the enterprise carbon emission reduction measure acquisition module is used for respectively inputting the evaluation results of each enterprise in the first evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set into the carbon emission reduction analysis model to obtain a carbon emission reduction measure set, wherein the carbon emission reduction measure of each enterprise comprises a plurality of measure parameters; the industry carbon emission reduction measure set acquisition module is used for clustering the enterprises according to the industries to obtain a plurality of industry clustering results and a plurality of industry carbon emission reduction measure sets; and the emission reduction measure fusion processing module is used for carrying out weighted calculation on measure parameters in the industry carbon emission reduction measure sets according to the enterprise scale in the industry clustering results to obtain industry carbon emission reduction fusion measures and carrying out carbon emission reduction.
The application also provides an electronic device, comprising:
a memory for storing executable instructions;
and the processor is used for realizing the industry fusion method based on carbon emission evaluation provided by the embodiment of the application when executing the executable instructions stored in the memory.
The application also provides a computer readable storage medium storing a computer program which, when executed by a processor, implements an industry fusion method based on carbon emission assessment provided by the embodiments of the application.
According to the industrial fusion method and system based on carbon emission assessment, the carbon emission quantity, the carbon emission intensity and the emission change rate in a preset time period are acquired, the assessment is respectively carried out according to three indexes, comprehensive assessment is carried out, three grades and the comprehensive grade of the carbon emission of an enterprise are acquired, corresponding carbon emission reduction measures are formulated according to different conditions, and then final industrial measures are obtained by weighting according to the scale of the enterprise in the industry. The carbon emission evaluation method and the carbon emission evaluation system realize more efficient carbon emission evaluation, acquire carbon emission reduction measures of different industries, and further improve the accuracy of acquiring the carbon emission reduction measures of the industries. The technical problems of low evaluation efficiency and inaccurate acquisition of carbon emission reduction measures in different industries in the prior art are solved.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
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In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments of the present disclosure will be briefly described below. It is apparent that the figures in the following description relate only to some embodiments of the present disclosure and are not limiting of the present disclosure.
FIG. 1 is a schematic flow chart of an industry fusion method based on carbon emission assessment according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of obtaining carbon emission data by an industry fusion method based on carbon emission assessment according to an embodiment of the present application;
FIG. 3 is a schematic flow chart of an industry fusion method based on carbon emission assessment to obtain a plurality of industry carbon emission reduction fusion measures according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a system of an industry fusion method based on carbon emission assessment according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a system electronic device of an industry fusion method based on carbon emission evaluation according to an embodiment of the present invention.
Reference numerals illustrate: the system comprises an emission data acquisition module 11, a carbon emission evaluation model construction module 12, an evaluation result acquisition module 13, an enterprise carbon emission reduction measure acquisition module 14, an industry carbon emission reduction measure set acquisition module 15 and an emission reduction measure fusion processing module 16.
Detailed Description
Example 1
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail with reference to the accompanying drawings, and the described embodiments should not be construed as limiting the present application, and all other embodiments obtained by those skilled in the art without making any inventive effort are within the scope of the present application.
In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is to be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments and can be combined with one another without conflict.
In the following description, the terms "first", "second", "third" and the like are merely used to distinguish similar objects and do not represent a particular ordering of the objects, it being understood that the "first", "second", "third" may be interchanged with a particular order or sequence, as permitted, to enable embodiments of the application described herein to be practiced otherwise than as illustrated or described herein.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the present application only.
While the present application makes various references to certain modules in a system according to embodiments of the present application, any number of different modules may be used and run on a user terminal and/or server, the modules are merely illustrative, and different aspects of the system and method may use different modules.
A flowchart is used in this application to describe the operations performed by a system according to embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed in order precisely. Rather, the various steps may be processed in reverse order or simultaneously, as desired. Also, other operations may be added to or removed from these processes.
As shown in fig. 1, an embodiment of the present application provides an industry fusion method based on carbon emission assessment, the method including:
s10, performing S10; acquiring carbon emission, carbon emission intensity and emission change rate of a plurality of enterprises in a target area in a preset time period, and acquiring a carbon emission set, a carbon emission intensity set and an emission change rate set;
S20, performing S20; constructing a carbon emission evaluation model, wherein the carbon emission evaluation model comprises a first evaluation unit, a second evaluation unit, a third evaluation unit and a comprehensive evaluation unit;
specifically, the carbon emission intensity and the emission change rate of a plurality of enterprises in the target area in a preset time period are obtained, wherein the preset time period can be set according to actual conditions, for example, the preset time period can be one quarter or one year. The carbon emission amount is the total amount of carbon emissions in a predetermined period, and the carbon emission intensity is the amount of carbon emissions discharged per unit of economic benefit, such as the amount of carbon emissions generated per ten thousand yuan of economic benefit. And the emission change rate is the carbon emission change condition generated in the adjacent preset time period. A carbon emission amount set, a carbon emission intensity set, and an emission change rate set are acquired. Subsequently, construction of a carbon emission evaluation model including a first evaluation unit, a second evaluation unit, a third evaluation unit, and a comprehensive evaluation unit is performed using the obtained carbon emission amount set, carbon emission intensity set, and emission change rate set.
As shown in fig. 2, the method S10 provided in the embodiment of the present application further includes:
S11, performing S11; collecting carbon emission of the enterprises in a current preset time period to obtain a carbon emission set;
s12, performing S12; acquiring the output of the enterprises in the current preset time period to obtain an output set;
s13, performing S13; collecting carbon emission of the enterprises in the last preset time period to obtain a historical carbon emission set;
s14, performing S14; and calculating to obtain the carbon emission intensity set according to the carbon emission amount set and the output set, and calculating to obtain the emission change rate set according to the carbon emission amount set and the historical carbon emission amount set.
Specifically, the carbon emission of a plurality of enterprises in a current preset time period is collected, and a carbon emission set of the enterprises is obtained. And acquiring the output of the enterprises in the current preset time period to obtain an output set, and acquiring the carbon emission of the enterprises in the previous preset time period to obtain a historical carbon emission set. And according to the carbon emission collection and the carbon emission output collection, calculating and obtaining the carbon emission intensity collection, namely carbon emission/output, wherein the unit is ton/ten thousand yuan. And calculating to obtain the emission change rate set according to the carbon emission amount set and the historical carbon emission amount set.
The method S20 provided in the embodiment of the present application further includes:
s21, performing S21; acquiring a plurality of sample carbon emissions, a plurality of sample carbon emission intensities, and a plurality of sample emission rates of change;
s22, performing S22; respectively carrying out single carbon emission evaluation and comprehensive carbon emission evaluation according to the carbon emission amounts, the carbon emission intensities and the change rates of the carbon emission to obtain a plurality of first evaluation results, a plurality of second evaluation results, a plurality of third evaluation results and a plurality of comprehensive evaluation results;
s23, performing S23; respectively constructing mapping relations among the plurality of sample carbon emission amounts, the plurality of sample first evaluation results, the plurality of sample carbon emission intensities, the plurality of sample second evaluation results, the plurality of sample emission change rates and the plurality of sample third evaluation results, and obtaining a first evaluation unit, a second evaluation unit and a third evaluation unit;
s24, performing S24; constructing the comprehensive evaluation unit by adopting the plurality of sample carbon emission amounts, the plurality of sample carbon emission intensities, the plurality of sample emission change rates and the plurality of sample comprehensive evaluation results;
s25, performing S25; and integrating the first evaluation unit, the second evaluation unit, the third evaluation unit and the comprehensive evaluation unit to obtain the carbon emission evaluation model.
Specifically, a plurality of sample carbon emissions, a plurality of sample carbon emission intensities, and a plurality of sample emission change rates are obtained. And respectively carrying out single carbon emission evaluation and comprehensive carbon emission evaluation according to the carbon emission amounts of the plurality of samples, the carbon emission intensities of the plurality of samples and the change rate of the carbon emission of the plurality of samples to obtain a plurality of first evaluation results of the samples, a plurality of second evaluation results of the samples, a plurality of third evaluation results of the samples and a plurality of comprehensive evaluation results of the samples, wherein the evaluation is carried out based on an expert in the carbon emission field when the single carbon emission evaluation and the comprehensive carbon emission evaluation are carried out, and the evaluation results can be scores, grades or the like. Wherein, the greater the emission, the lower the grade or score, the greater the emission intensity, the lower the grade or score, the positive the emission rate of change and the greater the rate of change, the lower the grade or score. The method comprises the steps of obtaining a plurality of sample first evaluation results, a plurality of sample second evaluation results, a plurality of sample third evaluation results and a plurality of sample comprehensive evaluation results. And then, respectively constructing mapping relations of a plurality of sample carbon emission amounts, a plurality of sample first evaluation results, a plurality of sample carbon emission intensities, a plurality of sample second evaluation results, a plurality of sample emission change rates and a plurality of sample third evaluation results, and obtaining the first evaluation unit, the second evaluation unit and the third evaluation unit. Further, the comprehensive evaluation unit is constructed using a plurality of sample carbon emissions, a plurality of sample carbon emission intensities, a plurality of sample emission change rates, and a plurality of sample comprehensive evaluation results. And integrating the first evaluation unit, the second evaluation unit, the third evaluation unit and the comprehensive evaluation unit to obtain the carbon emission evaluation model.
The method S24 provided in the embodiment of the present application further includes:
s241; constructing a first coordinate axis, a second coordinate axis and a third coordinate axis of an evaluation coordinate system based on the carbon emission amount, the sample carbon emission intensity and the emission change rate;
s242; combining the plurality of sample carbon emission amounts, the plurality of sample carbon emission intensities and the plurality of sample emission change rates to obtain a plurality of sample comprehensive evaluation data, and inputting the evaluation coordinate system to obtain a plurality of comprehensive coordinate points;
s243; and marking the plurality of comprehensive coordinate points by adopting the comprehensive evaluation results of the plurality of samples as a plurality of labels to obtain the constructed comprehensive evaluation unit.
Specifically, a first coordinate axis, a second coordinate axis, and a third coordinate axis of the evaluation coordinate system are constructed based on the carbon emission amount, the sample carbon emission intensity, and the emission change rate. The coordinate values on the first coordinate axis, the second coordinate axis and the third coordinate axis correspond to specific data values of the carbon emission amount, the sample carbon emission intensity and the emission change rate respectively. And combining the plurality of sample carbon emission amounts, the plurality of sample carbon emission intensities and the plurality of sample emission change rates to obtain a plurality of sample comprehensive evaluation data, wherein each sample comprehensive evaluation data corresponds to a group of carbon emission amounts, sample carbon emission intensities and emission change rates of an enterprise, inputting the sample comprehensive evaluation data into an evaluation coordinate system to obtain a plurality of comprehensive coordinate points, namely inputting the evaluation data which is subjected to expert evaluation into the evaluation coordinate system to obtain a plurality of comprehensive coordinate points. And marking the plurality of comprehensive coordinate points by adopting a plurality of sample comprehensive evaluation results as a plurality of labels, wherein the comprehensive coordinate points comprise corresponding comprehensive evaluation result labels at the moment, and the constructed comprehensive evaluation unit is obtained.
S30, performing S30; inputting the data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set into the first evaluation unit, the second evaluation unit and the third evaluation unit respectively, and merging and inputting the data into the comprehensive evaluation unit to obtain a first evaluation result set, a second evaluation result set, a third evaluation result set and a comprehensive evaluation result set;
s40, performing S40; inputting the evaluation results of each enterprise in the first evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set into a carbon emission reduction analysis model to obtain a carbon emission reduction measure set, wherein the carbon emission reduction measure of each enterprise comprises a plurality of measure parameters;
s50, performing S50; clustering the enterprises according to a plurality of industries to obtain a plurality of industry clustering results and a plurality of industry carbon emission reduction measure sets;
s60, performing S60; and weighting calculation is carried out on measure parameters in the industry carbon emission reduction measure sets according to the enterprise scale in the industry clustering results to obtain industry carbon emission reduction fusion measures, and carbon emission reduction is carried out.
Specifically, data in a carbon emission amount set, a carbon emission intensity set and an emission change rate set are respectively input into the first evaluation unit, the second evaluation unit and the third evaluation unit, and are input into the comprehensive evaluation unit in a merging way, so that a first evaluation result set, a second evaluation result set, a third evaluation result set and a comprehensive evaluation result set are obtained. And then, inputting the acquired evaluation results of each enterprise in the evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set into a carbon emission reduction analysis model to obtain a carbon emission reduction measure set, and obtaining a carbon emission reduction measure set corresponding to the evaluation results of the enterprise, wherein the carbon emission reduction measure of each enterprise comprises a plurality of measure parameters. Further, a plurality of enterprises are clustered according to a plurality of industries to obtain a plurality of industry clustering results, and a plurality of industry carbon emission reduction measure sets are obtained, namely, according to the carbon emission reduction measure of each enterprise in the industry, all enterprise carbon emission reduction measure sets of the industry are obtained. And finally, according to the enterprise scale in the clustering results of the industries, weighting and calculating measure parameters in the carbon emission reduction measure sets of the industries, so that the finally obtained carbon emission reduction measure sets and industries have higher matching degree, and a plurality of industry carbon emission reduction fusion measures are obtained to carry out carbon emission reduction. The method has the advantages that the weight is carried out through the enterprise scale, the carbon emission reduction measures suitable for the industry are formulated, the method is accurate and intelligent, the parameters of the industry emission reduction measures are uniform, the promotion, the realization, the communication and the management are convenient, the more efficient carbon emission assessment is realized, the carbon emission reduction measures of different industries are acquired, and the accuracy of the acquisition of the industry carbon emission reduction measures is further improved.
The method S30 provided in the embodiment of the present application further includes:
s31, performing S31; inputting data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set into the first evaluation unit, the second evaluation unit and the third evaluation unit respectively to obtain a closest sample carbon emission amount set, a sample carbon emission intensity set and a sample emission change rate set;
s32, performing S32; obtaining a first evaluation result set, a second evaluation result set and a third evaluation result set according to the mapping relation in the first evaluation unit, the second evaluation unit and the third evaluation unit;
s33, performing S33; dividing the data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set according to the enterprises, and inputting the data into the comprehensive evaluation unit to obtain a plurality of enterprise coordinate points;
s34, performing S34; acquiring K nearest comprehensive coordinate points or overlapped comprehensive coordinate points of the enterprise coordinate points, wherein K is an odd number;
s35, performing S35; and taking the sample comprehensive evaluation result with the highest occurrence frequency in the K sample comprehensive evaluation results corresponding to the K nearest comprehensive coordinate points as a comprehensive evaluation result, or taking the sample comprehensive evaluation result corresponding to the overlapped comprehensive coordinate points as a comprehensive evaluation result to obtain the comprehensive evaluation result set.
Specifically, data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set are respectively input into the first evaluation unit, the second evaluation unit and the third evaluation unit to obtain the closest sample carbon emission amount set, the sample carbon emission intensity set and the sample emission change rate set, and data of the carbon emission amount set, the carbon emission intensity set and the emission change rate set closest to the sample are obtained. And acquiring a first evaluation result set, a second evaluation result set and a third evaluation result set corresponding to the closest sample carbon emission amount set, the sample carbon emission intensity set and the sample emission change rate set according to the mapping relation in the first evaluation unit, the second evaluation unit and the third evaluation unit.
Further, the data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set are divided according to the enterprises, and are input into the comprehensive evaluation unit, so that a plurality of enterprise coordinate points are obtained. And acquiring K nearest comprehensive coordinate points or overlapped comprehensive coordinate points of the enterprise coordinate points, wherein K is an odd number. And if the enterprise coordinate points do not coincide with any comprehensive coordinate points, taking the sample comprehensive evaluation result with highest occurrence frequency in K sample comprehensive evaluation results corresponding to the K nearest comprehensive coordinate points as a comprehensive evaluation result, or if the enterprise coordinate points coincide with a certain comprehensive coordinate point, taking the sample comprehensive evaluation result corresponding to the comprehensive coordinate points overlapped by the enterprise coordinate points as a corresponding comprehensive evaluation result, thus obtaining comprehensive evaluation results corresponding to a plurality of enterprises, and obtaining a comprehensive evaluation result set, namely obtaining a plurality of enterprise data and distances of the comprehensive coordinate points, and comprehensively evaluating the plurality of enterprise data according to the distances, thereby realizing comprehensive evaluation of the plurality of enterprise data.
The method S40 provided in the embodiment of the present application further includes:
s41, performing S41; combining according to the first evaluation results of the samples, the second evaluation results of the samples, the third evaluation results of the samples and the comprehensive evaluation results of the samples to obtain a plurality of sample evaluation result sets;
s42, performing S42; acquiring a plurality of corresponding sample carbon emission reduction measures according to the plurality of sample evaluation result sets, wherein the plurality of sample carbon emission reduction measures comprise different sample measure parameter sets;
s43; labeling data of the plurality of sample evaluation result sets and the plurality of sample carbon emission reduction measures to obtain a constructed data set;
s44; based on a BP neural network, constructing the carbon emission reduction analysis model, wherein input data of the carbon emission reduction analysis model is an evaluation result set, and output data is carbon emission reduction measures;
s45; performing iterative supervision training and verification on the carbon emission reduction analysis model by adopting the constructed data set until the carbon emission reduction analysis model converges or the accuracy reaches a preset requirement, so as to obtain the carbon emission reduction analysis model;
s46, performing S46; dividing and combining the evaluation results in the evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set according to the enterprises to obtain a plurality of evaluation result sets, and inputting the carbon emission reduction analysis model to obtain the carbon emission reduction measure set.
Specifically, a plurality of sample evaluation result sets are obtained by combining a plurality of sample first evaluation results, a plurality of sample second evaluation results, a plurality of sample third evaluation results and a plurality of sample comprehensive evaluation results, wherein each sample evaluation result set comprises a sample first evaluation result, a sample second evaluation result, a sample third evaluation result and a sample comprehensive evaluation result. And formulating and acquiring a plurality of corresponding sample carbon emission reduction measures according to a plurality of sample evaluation result sets, wherein the plurality of sample carbon emission reduction measures comprise different sample measure parameter sets, namely, each sample evaluation result set corresponds to one sample carbon emission reduction measure, wherein the sample carbon emission reduction measure can be acquired after the sample evaluation result set is analyzed by an expert in the field of carbon emission reduction, the sample carbon emission reduction measure comprises measures for limiting the fuel consumption of enterprises, carbon emission quota and the like, and the corresponding sample measure parameters comprise parameters such as percentage of the fuel consumption, percentage value of carbon emission quota adjustment and the like, wherein the percentage value of the fuel consumption is specifically limited and the like.
And marking data of the plurality of sample evaluation result sets and the plurality of sample carbon emission reduction measures to obtain a constructed data set. Further, based on the BP neural network, the carbon emission reduction analysis model is constructed, wherein input data of the carbon emission reduction analysis model is an evaluation result set, and output data is carbon emission reduction measures. When the carbon emission reduction analysis model is obtained, the constructed BP neural network is subjected to supervision training by constructing a data set until the output result of the model meets a certain accuracy, and the carbon emission reduction analysis model is obtained. And finally, dividing and combining the evaluation results in the evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set according to a plurality of enterprises, and dividing and combining the evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set according to different enterprise data. And obtaining a plurality of evaluation result sets, inputting the carbon emission reduction analysis model, and obtaining the carbon emission reduction measure set, thereby realizing the more accurate carbon emission reduction measure set obtained by using the evaluation data.
As shown in fig. 3, the method S60 provided in the embodiment of the present application further includes:
s61, performing S61; acquiring scale information of the enterprises to obtain a plurality of scale information;
s62, performing S62; according to the size of enterprise scale information in the industry clustering results, weight distribution is carried out to obtain a plurality of weight distribution results, wherein the larger the scale information is, the larger the corresponding weight coefficient is;
s63; adopting the multiple weight distribution results to respectively carry out weighted calculation on measure parameters in multiple industry carbon emission reduction measure sets to obtain multiple weighted measure parameter sets;
s64; and obtaining the industry carbon emission reduction fusion measures according to the weighted measure parameter sets.
Specifically, the scale information of a plurality of enterprises is obtained, and a plurality of scale information is obtained. And carrying out weight distribution according to the size of the enterprise scale information in the plurality of industry clustering results, namely carrying out weight distribution according to the size of the enterprise according to the clustering results of the enterprise to obtain a plurality of weight distribution results, wherein the larger the scale information is, the larger the corresponding weight coefficient is. And respectively carrying out weighted calculation on measure parameters in the plurality of industry carbon emission reduction measure sets by adopting a plurality of weight distribution results to obtain a plurality of weighted measure parameter sets. And obtaining the carbon emission reduction fusion measures of the industries according to the obtained multiple weighted measure parameter sets, and further obtaining the carbon emission reduction fusion measures of different industries. The method has the advantages that the weight is carried out through the enterprise scale, the carbon emission reduction measures suitable for the industry are formulated, the method is accurate and intelligent, the parameters of the industry emission reduction measures are uniform, the promotion, the realization, the communication and the management are convenient, the more efficient carbon emission assessment is realized, the carbon emission reduction measures of different industries are acquired, and the accuracy of the acquisition of the industry carbon emission reduction measures is further improved.
According to the technical scheme provided by the embodiment of the invention, the carbon emission quantity set, the carbon emission intensity set and the emission change rate set are obtained. And constructing a carbon emission evaluation model, wherein the carbon emission evaluation model comprises a first evaluation unit, a second evaluation unit, a third evaluation unit and a comprehensive evaluation unit. And respectively inputting the data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set into the first evaluation unit, the second evaluation unit and the third evaluation unit, and merging and inputting the data into the comprehensive evaluation unit to obtain a first evaluation result set, a second evaluation result set, a third evaluation result set and a comprehensive evaluation result set. And respectively inputting the evaluation results of each enterprise in the first evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set into a carbon emission reduction analysis model to obtain a carbon emission reduction measure set, wherein the carbon emission reduction measure of each enterprise comprises a plurality of measure parameters. And according to the size of enterprise scale in the industry clustering results, weighting calculation is carried out on measure parameters in the industry carbon emission reduction measure sets to obtain a plurality of industry carbon emission reduction fusion measures, and carbon emission reduction is carried out. The carbon emission evaluation method and the carbon emission evaluation system realize more efficient carbon emission evaluation, acquire carbon emission reduction measures of different industries, and further improve the accuracy of acquiring the carbon emission reduction measures of the industries. The technical problems of low evaluation efficiency and inaccurate acquisition of carbon emission reduction measures in different industries in the prior art are solved.
Example two
Based on the same concept as the industry fusion method based on carbon emission assessment in the foregoing embodiment, the present invention further provides a system of the industry fusion method based on carbon emission assessment, which may be implemented by hardware and/or software, and may be generally integrated in an electronic device, for executing the method provided by any embodiment of the present invention. As shown in fig. 4, the system includes:
an emission data acquisition module 11 for acquiring carbon emission, carbon emission intensity, and emission change rate of a plurality of enterprises in a target area within a preset time period, and obtaining a carbon emission amount set, a carbon emission intensity set, and an emission change rate set;
a carbon emission estimation model construction module 12 for constructing a carbon emission estimation model, wherein the carbon emission estimation model includes a first estimation unit, a second estimation unit, a third estimation unit, and a comprehensive estimation unit;
an evaluation result acquisition module 13, configured to input data in the carbon emission amount set, the carbon emission intensity set, and the emission change rate set into the first evaluation unit, the second evaluation unit, and the third evaluation unit, respectively, and to input the data in the integrated evaluation unit in a merging manner, so as to obtain a first evaluation result set, a second evaluation result set, a third evaluation result set, and an integrated evaluation result set;
An enterprise carbon emission reduction measure obtaining module 14, configured to input, into a carbon emission reduction analysis model, an evaluation result of each enterprise in the first evaluation result set, the second evaluation result set, the third evaluation result set, and the comprehensive evaluation result set, to obtain a carbon emission reduction measure set, where the carbon emission reduction measure of each enterprise includes a plurality of measure parameters;
the industry carbon emission reduction measure set acquisition module 15 is used for clustering the enterprises according to a plurality of industries to obtain a plurality of industry clustering results and a plurality of industry carbon emission reduction measure sets;
and the emission reduction measure fusion processing module 16 is used for carrying out weighted calculation on measure parameters in the industry carbon emission reduction measure sets according to the sizes of enterprise scales in the industry clustering results to obtain industry carbon emission reduction fusion measures and carrying out carbon emission reduction.
Further, the emission data acquisition module 11 is further configured to:
collecting carbon emission of the enterprises in a current preset time period to obtain a carbon emission set;
acquiring the output of the enterprises in the current preset time period to obtain an output set;
collecting carbon emission of the enterprises in the last preset time period to obtain a historical carbon emission set;
And calculating to obtain the carbon emission intensity set according to the carbon emission amount set and the output set, and calculating to obtain the emission change rate set according to the carbon emission amount set and the historical carbon emission amount set.
Further, the carbon emission estimation model construction module 12 is further configured to:
acquiring a plurality of sample carbon emissions, a plurality of sample carbon emission intensities, and a plurality of sample emission rates of change;
respectively carrying out single carbon emission evaluation and comprehensive carbon emission evaluation according to the carbon emission amounts, the carbon emission intensities and the change rates of the carbon emission to obtain a plurality of first evaluation results, a plurality of second evaluation results, a plurality of third evaluation results and a plurality of comprehensive evaluation results;
respectively constructing mapping relations among the plurality of sample carbon emission amounts, the plurality of sample first evaluation results, the plurality of sample carbon emission intensities, the plurality of sample second evaluation results, the plurality of sample emission change rates and the plurality of sample third evaluation results, and obtaining a first evaluation unit, a second evaluation unit and a third evaluation unit;
constructing the comprehensive evaluation unit by adopting the plurality of sample carbon emission amounts, the plurality of sample carbon emission intensities, the plurality of sample emission change rates and the plurality of sample comprehensive evaluation results;
And integrating the first evaluation unit, the second evaluation unit, the third evaluation unit and the comprehensive evaluation unit to obtain the carbon emission evaluation model.
Further, the carbon emission estimation model construction module 12 is further configured to:
constructing a first coordinate axis, a second coordinate axis and a third coordinate axis of an evaluation coordinate system based on the carbon emission amount, the sample carbon emission intensity and the emission change rate;
combining the plurality of sample carbon emission amounts, the plurality of sample carbon emission intensities and the plurality of sample emission change rates to obtain a plurality of sample comprehensive evaluation data, and inputting the evaluation coordinate system to obtain a plurality of comprehensive coordinate points;
and marking the plurality of comprehensive coordinate points by adopting the comprehensive evaluation results of the plurality of samples as a plurality of labels to obtain the constructed comprehensive evaluation unit.
Further, the evaluation result acquisition module 13 is further configured to:
inputting data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set into the first evaluation unit, the second evaluation unit and the third evaluation unit respectively to obtain a closest sample carbon emission amount set, a sample carbon emission intensity set and a sample emission change rate set;
Obtaining a first evaluation result set, a second evaluation result set and a third evaluation result set according to the mapping relation in the first evaluation unit, the second evaluation unit and the third evaluation unit;
dividing the data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set according to the enterprises, and inputting the data into the comprehensive evaluation unit to obtain a plurality of enterprise coordinate points;
acquiring K nearest comprehensive coordinate points or overlapped comprehensive coordinate points of the enterprise coordinate points, wherein K is an odd number;
and taking the sample comprehensive evaluation result with the highest occurrence frequency in the K sample comprehensive evaluation results corresponding to the K nearest comprehensive coordinate points as a comprehensive evaluation result, or taking the sample comprehensive evaluation result corresponding to the overlapped comprehensive coordinate points as a comprehensive evaluation result to obtain the comprehensive evaluation result set.
Further, the enterprise carbon emission reduction measure acquisition module 14 is further configured to:
combining according to the first evaluation results of the samples, the second evaluation results of the samples, the third evaluation results of the samples and the comprehensive evaluation results of the samples to obtain a plurality of sample evaluation result sets;
Acquiring a plurality of corresponding sample carbon emission reduction measures according to the plurality of sample evaluation result sets, wherein the plurality of sample carbon emission reduction measures comprise different sample measure parameter sets;
labeling data of the plurality of sample evaluation result sets and the plurality of sample carbon emission reduction measures to obtain a constructed data set;
based on a BP neural network, constructing the carbon emission reduction analysis model, wherein input data of the carbon emission reduction analysis model is an evaluation result set, and output data is carbon emission reduction measures;
performing iterative supervision training and verification on the carbon emission reduction analysis model by adopting the constructed data set until the carbon emission reduction analysis model converges or the accuracy reaches a preset requirement, so as to obtain the carbon emission reduction analysis model;
dividing and combining the evaluation results in the evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set according to the enterprises to obtain a plurality of evaluation result sets, and inputting the carbon emission reduction analysis model to obtain the carbon emission reduction measure set.
Further, the emission reduction measure fusion processing module 16 is further configured to:
acquiring scale information of the enterprises to obtain a plurality of scale information;
According to the size of enterprise scale information in the industry clustering results, weight distribution is carried out to obtain a plurality of weight distribution results, wherein the larger the scale information is, the larger the corresponding weight coefficient is;
adopting the multiple weight distribution results to respectively carry out weighted calculation on measure parameters in multiple industry carbon emission reduction measure sets to obtain multiple weighted measure parameter sets;
and obtaining the industry carbon emission reduction fusion measures according to the weighted measure parameter sets.
The included units and modules are only divided according to the functional logic, but are not limited to the above-mentioned division, so long as the corresponding functions can be realized; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
Example III
Fig. 5 is a schematic structural diagram of an electronic device provided in a third embodiment of the present invention, and shows a block diagram of an exemplary electronic device suitable for implementing an embodiment of the present invention. The electronic device shown in fig. 5 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention. As shown in fig. 5, the electronic device includes a processor 31, a memory 32, an input device 33, and an output device 34; the number of processors 31 in the electronic device may be one or more, in fig. 5, one processor 31 is taken as an example, and the processors 31, the memory 32, the input device 33 and the output device 34 in the electronic device may be connected by a bus or other means, in fig. 5, by bus connection is taken as an example.
The memory 32 is used as a computer readable storage medium for storing software programs, computer executable programs and modules, such as program instructions/modules corresponding to an industry fusion method based on carbon emission assessment in an embodiment of the present invention. The processor 31 executes various functional applications of the computer device and data processing by running software programs, instructions and modules stored in the memory 32, i.e. implements an industry fusion method based on carbon emission assessment as described above.
The foregoing has shown and described the basic principles and main features of the present invention and the advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (10)
1. An industry fusion method based on carbon emission assessment, the method comprising:
acquiring carbon emission, carbon emission intensity and emission change rate of a plurality of enterprises in a target area in a preset time period, and acquiring a carbon emission set, a carbon emission intensity set and an emission change rate set;
Constructing a carbon emission evaluation model, wherein the carbon emission evaluation model comprises a first evaluation unit, a second evaluation unit, a third evaluation unit and a comprehensive evaluation unit;
inputting the data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set into the first evaluation unit, the second evaluation unit and the third evaluation unit respectively, and merging and inputting the data into the comprehensive evaluation unit to obtain a first evaluation result set, a second evaluation result set, a third evaluation result set and a comprehensive evaluation result set;
inputting the evaluation results of each enterprise in the first evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set into a carbon emission reduction analysis model to obtain a carbon emission reduction measure set, wherein the carbon emission reduction measure of each enterprise comprises a plurality of measure parameters;
clustering the enterprises according to a plurality of industries to obtain a plurality of industry clustering results and a plurality of industry carbon emission reduction measure sets;
and weighting calculation is carried out on measure parameters in the industry carbon emission reduction measure sets according to the enterprise scale in the industry clustering results to obtain industry carbon emission reduction fusion measures, and carbon emission reduction is carried out.
2. The method of claim 1, wherein obtaining the carbon emissions, the carbon emission intensity, and the emission rate of the plurality of businesses in the target area over the predetermined period of time comprises:
collecting carbon emission of the enterprises in a current preset time period to obtain a carbon emission set;
acquiring the output of the enterprises in the current preset time period to obtain an output set;
collecting carbon emission of the enterprises in the last preset time period to obtain a historical carbon emission set;
and calculating to obtain the carbon emission intensity set according to the carbon emission amount set and the output set, and calculating to obtain the emission change rate set according to the carbon emission amount set and the historical carbon emission amount set.
3. The method of claim 1, wherein the constructing a carbon emission assessment model comprises:
acquiring a plurality of sample carbon emissions, a plurality of sample carbon emission intensities, and a plurality of sample emission rates of change;
respectively carrying out single carbon emission evaluation and comprehensive carbon emission evaluation according to the carbon emission amounts, the carbon emission intensities and the change rates of the carbon emission to obtain a plurality of first evaluation results, a plurality of second evaluation results, a plurality of third evaluation results and a plurality of comprehensive evaluation results;
Respectively constructing mapping relations among the plurality of sample carbon emission amounts, the plurality of sample first evaluation results, the plurality of sample carbon emission intensities, the plurality of sample second evaluation results, the plurality of sample emission change rates and the plurality of sample third evaluation results, and obtaining a first evaluation unit, a second evaluation unit and a third evaluation unit;
constructing the comprehensive evaluation unit by adopting the plurality of sample carbon emission amounts, the plurality of sample carbon emission intensities, the plurality of sample emission change rates and the plurality of sample comprehensive evaluation results;
and integrating the first evaluation unit, the second evaluation unit, the third evaluation unit and the comprehensive evaluation unit to obtain the carbon emission evaluation model.
4. The method of claim 3, wherein constructing the integrated evaluation unit using the plurality of sample carbon emissions, the plurality of sample carbon emission intensities, the plurality of sample emission rates of change, and the plurality of sample integrated evaluation results comprises:
constructing a first coordinate axis, a second coordinate axis and a third coordinate axis of an evaluation coordinate system based on the carbon emission amount, the sample carbon emission intensity and the emission change rate;
combining the plurality of sample carbon emission amounts, the plurality of sample carbon emission intensities and the plurality of sample emission change rates to obtain a plurality of sample comprehensive evaluation data, and inputting the evaluation coordinate system to obtain a plurality of comprehensive coordinate points;
And marking the plurality of comprehensive coordinate points by adopting the comprehensive evaluation results of the plurality of samples as a plurality of labels to obtain the constructed comprehensive evaluation unit.
5. The method of claim 4, wherein inputting data in the carbon emission amount set, the carbon emission intensity set, and the emission change rate set into the first evaluation unit, the second evaluation unit, and the third evaluation unit, respectively, and merging into the comprehensive evaluation unit, obtaining a first evaluation result set, a second evaluation result set, a third evaluation result set, and a comprehensive evaluation result set, comprises:
inputting data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set into the first evaluation unit, the second evaluation unit and the third evaluation unit respectively to obtain a closest sample carbon emission amount set, a sample carbon emission intensity set and a sample emission change rate set;
obtaining a first evaluation result set, a second evaluation result set and a third evaluation result set according to the mapping relation in the first evaluation unit, the second evaluation unit and the third evaluation unit;
dividing the data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set according to the enterprises, and inputting the data into the comprehensive evaluation unit to obtain a plurality of enterprise coordinate points;
Acquiring K nearest comprehensive coordinate points or overlapped comprehensive coordinate points of the enterprise coordinate points, wherein K is an odd number;
and taking the sample comprehensive evaluation result with the highest occurrence frequency in the K sample comprehensive evaluation results corresponding to the K nearest comprehensive coordinate points as a comprehensive evaluation result, or taking the sample comprehensive evaluation result corresponding to the overlapped comprehensive coordinate points as a comprehensive evaluation result to obtain the comprehensive evaluation result set.
6. The method of claim 3, wherein inputting the evaluation results of each enterprise in the first, second, third, and comprehensive evaluation result sets into a carbon emission reduction analysis model to obtain a carbon emission reduction measure set, respectively, comprises:
combining according to the first evaluation results of the samples, the second evaluation results of the samples, the third evaluation results of the samples and the comprehensive evaluation results of the samples to obtain a plurality of sample evaluation result sets;
acquiring a plurality of corresponding sample carbon emission reduction measures according to the plurality of sample evaluation result sets, wherein the plurality of sample carbon emission reduction measures comprise different sample measure parameter sets;
Labeling data of the plurality of sample evaluation result sets and the plurality of sample carbon emission reduction measures to obtain a constructed data set;
based on a BP neural network, constructing the carbon emission reduction analysis model, wherein input data of the carbon emission reduction analysis model is an evaluation result set, and output data is carbon emission reduction measures;
performing iterative supervision training and verification on the carbon emission reduction analysis model by adopting the constructed data set until the carbon emission reduction analysis model converges or the accuracy reaches a preset requirement, so as to obtain the carbon emission reduction analysis model;
dividing and combining the evaluation results in the evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set according to the enterprises to obtain a plurality of evaluation result sets, and inputting the carbon emission reduction analysis model to obtain the carbon emission reduction measure set.
7. The method of claim 1, wherein weighting the measure parameters in the plurality of industry carbon emission reduction measure sets according to the size of the enterprise scale in the plurality of industry cluster results comprises:
acquiring scale information of the enterprises to obtain a plurality of scale information;
According to the size of enterprise scale information in the industry clustering results, weight distribution is carried out to obtain a plurality of weight distribution results, wherein the larger the scale information is, the larger the corresponding weight coefficient is;
adopting the multiple weight distribution results to respectively carry out weighted calculation on measure parameters in multiple industry carbon emission reduction measure sets to obtain multiple weighted measure parameter sets;
and obtaining the industry carbon emission reduction fusion measures according to the weighted measure parameter sets.
8. An industry fusion system based on carbon emission assessment, the system comprising:
an emission data acquisition module, configured to acquire carbon emission, carbon emission intensity and emission change rate of a plurality of enterprises in a target area within a preset time period, and obtain a carbon emission set, a carbon emission intensity set and an emission change rate set;
the carbon emission evaluation model construction module is used for constructing a carbon emission evaluation model, wherein the carbon emission evaluation model comprises a first evaluation unit, a second evaluation unit, a third evaluation unit and a comprehensive evaluation unit;
the evaluation result acquisition module is used for respectively inputting the data in the carbon emission amount set, the carbon emission intensity set and the emission change rate set into the first evaluation unit, the second evaluation unit and the third evaluation unit, and merging and inputting the data into the comprehensive evaluation unit to obtain a first evaluation result set, a second evaluation result set, a third evaluation result set and a comprehensive evaluation result set;
The enterprise carbon emission reduction measure acquisition module is used for respectively inputting the evaluation results of each enterprise in the first evaluation result set, the second evaluation result set, the third evaluation result set and the comprehensive evaluation result set into the carbon emission reduction analysis model to obtain a carbon emission reduction measure set, wherein the carbon emission reduction measure of each enterprise comprises a plurality of measure parameters;
the industry carbon emission reduction measure set acquisition module is used for clustering the enterprises according to the industries to obtain a plurality of industry clustering results and a plurality of industry carbon emission reduction measure sets;
and the emission reduction measure fusion processing module is used for carrying out weighted calculation on measure parameters in the industry carbon emission reduction measure sets according to the enterprise scale in the industry clustering results to obtain industry carbon emission reduction fusion measures and carrying out carbon emission reduction.
9. An electronic device, the electronic device comprising:
a memory for storing executable instructions;
a processor for implementing an industry fusion method based on carbon emission assessment as claimed in any one of claims 1 to 7 when executing executable instructions stored in said memory.
10. A computer readable medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements an industry fusion method based on carbon emission assessment according to any one of claims 1-7.
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