CN117350594A - Electric energy substitution technology evaluation method and device based on cloud model-entropy weight method - Google Patents
Electric energy substitution technology evaluation method and device based on cloud model-entropy weight method Download PDFInfo
- Publication number
- CN117350594A CN117350594A CN202311417448.9A CN202311417448A CN117350594A CN 117350594 A CN117350594 A CN 117350594A CN 202311417448 A CN202311417448 A CN 202311417448A CN 117350594 A CN117350594 A CN 117350594A
- Authority
- CN
- China
- Prior art keywords
- evaluation
- electric energy
- index
- energy substitution
- target
- 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
- 238000011156 evaluation Methods 0.000 title claims abstract description 635
- 238000006467 substitution reaction Methods 0.000 title claims abstract description 273
- 238000005516 engineering process Methods 0.000 title claims abstract description 207
- 238000000034 method Methods 0.000 title claims abstract description 100
- 238000013210 evaluation model Methods 0.000 claims abstract description 47
- 239000011159 matrix material Substances 0.000 claims description 66
- 239000013598 vector Substances 0.000 claims description 14
- 230000008569 process Effects 0.000 claims description 11
- 230000002194 synthesizing effect Effects 0.000 claims description 9
- 238000010276 construction Methods 0.000 claims description 6
- 238000003860 storage Methods 0.000 claims description 4
- 230000008901 benefit Effects 0.000 abstract description 10
- 238000012545 processing Methods 0.000 description 8
- 238000010606 normalization Methods 0.000 description 7
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 4
- 229910052799 carbon Inorganic materials 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000007613 environmental effect Effects 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 230000002776 aggregation Effects 0.000 description 2
- 238000004220 aggregation Methods 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000012854 evaluation process Methods 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 239000005431 greenhouse gas Substances 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000007620 mathematical function Methods 0.000 description 1
- 238000012821 model calculation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000000513 principal component analysis Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
- 230000009897 systematic effect Effects 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
-
- 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
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
- Y02P90/82—Energy audits or management systems therefor
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Mathematical Physics (AREA)
- Mathematical Optimization (AREA)
- Health & Medical Sciences (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- Pure & Applied Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Data Mining & Analysis (AREA)
- Computational Mathematics (AREA)
- Development Economics (AREA)
- Mathematical Analysis (AREA)
- Entrepreneurship & Innovation (AREA)
- Software Systems (AREA)
- Game Theory and Decision Science (AREA)
- Computing Systems (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Quality & Reliability (AREA)
- General Engineering & Computer Science (AREA)
- Water Supply & Treatment (AREA)
- Public Health (AREA)
- Operations Research (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
In the electric energy substitution technology evaluation method and device based on the cloud model-entropy weight method, a plurality of target electric energy substitution technology evaluation indexes are determined in a plurality of pre-acquired electric energy substitution technology evaluation indexes, and a target electric energy substitution technology evaluation object and a comprehensive evaluation grade are determined; determining a fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technical evaluation index, wherein the fuzzy comprehensive evaluation model is constructed by a cloud model-entropy weight method; evaluating the target electric energy substitution technology evaluation object by adopting a fuzzy comprehensive evaluation model to obtain a target evaluation grade of the target electric energy substitution technology evaluation object; and determining the evaluation score of the target electric energy substitution technology evaluation object according to the target evaluation grade and the comprehensive evaluation grade, so as to analyze the evaluation result according to the evaluation score. Thus, a complete and scientific evaluation method and index system can be formed to evaluate the comprehensive benefit of the electric energy substitution technology.
Description
Technical Field
The application relates to the technical field of evaluation of electric energy replacement benefits, in particular to an electric energy replacement technical evaluation method and device based on a cloud model-entropy weight method.
Background
To promote the development of new energy and reduce carbon emissions, an electric energy replacement technology is considered as an important measure to replace fossil energy with high pollution and high carbon emissions by using electric energy in the use of terminal energy, so as to obtain benefits of low carbon, environmental protection and economic safety. Electric energy replacement technology is widely accepted as a means of effectively reducing greenhouse gas emissions and has been demonstrated in various fields. Therefore, the comprehensive benefit of the electric energy replacement technology is evaluated, and a corresponding propulsion strategy is formulated, so that the method becomes one of the problems to be researched.
Some researches are carried out on evaluating electric energy substitution technologies, such as early work, engineering construction, production operation, economic benefit and the like, and the defects of electric power construction projects are analyzed; or a quantitative calculation model for researching the technical, economical and environmental indexes of the comprehensive energy system; the influence of supply side reform factors on power development is quantitatively analyzed by a comprehensive method of combining linear and nonlinear direct correlation factors, systematic principal component analysis and the like. However, a complete and scientific evaluation method and index system are not formed in the prior study so as to evaluate the comprehensive benefit of the electric energy substitution technology.
Disclosure of Invention
The present application aims to solve at least one of the above technical drawbacks, and in particular, the technical drawbacks of the prior art that a complete and scientific evaluation method and index system have not been formed yet to evaluate the comprehensive benefits of the electric energy replacement technology.
In a first aspect, the present application provides a method for evaluating an electric energy substitution technology based on a cloud model-entropy weighting method, where the method includes:
determining a plurality of target electric energy substitution technical evaluation indexes from a plurality of pre-acquired electric energy substitution technical evaluation indexes, and determining target electric energy substitution technical evaluation objects and comprehensive evaluation grades;
determining a fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technology evaluation index, wherein the fuzzy comprehensive evaluation model is constructed based on target weights of each target electric energy substitution technology evaluation index and a target fuzzy relation matrix corresponding to each target electric energy substitution technology evaluation index and the comprehensive evaluation grade, each target weight is an average value of subjective weights and objective weights of each target electric energy substitution technology evaluation index, the subjective weights are comprehensive language evaluation cloud models corresponding to evaluation languages of each electric energy substitution technology evaluation index based on a plurality of experts, and index evaluation cloud models corresponding to each electric energy substitution technology evaluation index, the objective weights are obtained by normalizing the index evaluation cloud models corresponding to each target electric energy substitution technology evaluation index by adopting an entropy weight method, and sample data of each target electric energy substitution technology evaluation index obtained in advance;
Evaluating the target electric energy substitution technology evaluation object by adopting the fuzzy comprehensive evaluation model to obtain a target evaluation grade of the target electric energy substitution technology evaluation object;
and determining the evaluation value of the target electric energy substitution technology evaluation object according to the target evaluation grade and the comprehensive evaluation grade, so as to analyze the evaluation result according to the evaluation value.
In one embodiment, the construction process of the fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technical evaluation index includes:
converting the target weight of each target electric energy substitution technical evaluation index into a fuzzy weight vector;
and synthesizing the fuzzy weight vector and the target fuzzy relation matrix to obtain the fuzzy comprehensive evaluation model.
In one embodiment, the determining the subjective weight of each target power replacement technical evaluation index includes:
acquiring the evaluation languages of each expert on each electric energy substitution technology evaluation index, and determining a language evaluation cloud model corresponding to the evaluation language of each expert on each electric energy substitution technology evaluation index;
synthesizing each language evaluation cloud model to obtain the comprehensive language evaluation cloud model;
Calculating an index evaluation cloud model corresponding to each electric energy substitution technical evaluation index according to a language evaluation cloud model corresponding to the evaluation language of each electric energy substitution technical evaluation index by each expert;
and normalizing the index evaluation cloud model corresponding to each target electric energy substitution technology evaluation index based on the comprehensive language evaluation cloud model and each index evaluation cloud model to obtain the subjective weight of each target electric energy substitution technology evaluation index.
In one embodiment, the step of calculating, according to a language evaluation cloud model corresponding to an evaluation language of each of the electrical energy substitution technical evaluation indexes by each of the experts, an index evaluation cloud model corresponding to each of the electrical energy substitution technical evaluation indexes includes:
calculating an index evaluation cloud model corresponding to each electric energy substitution technology evaluation index according to the following expression:
wherein Z is j Index evaluation cloud model for j-th electric energy substitution technical evaluation index, s is total number of experts, k is k-th expert, Z j k And a language evaluation language model corresponding to the evaluation language of the j-th electric energy substitution technology evaluation index is provided for the k-th expert.
In one embodiment, the step of normalizing the index evaluation cloud model corresponding to each target electrical energy substitution technical evaluation index based on the comprehensive language evaluation cloud model and each index evaluation cloud model to obtain subjective weight of each target electrical energy substitution technical evaluation index includes:
determining a standard evaluation cloud model in the comprehensive language evaluation cloud model and each index evaluation cloud model;
calculating the similarity between the index evaluation cloud model corresponding to each target electric energy substitution technical evaluation index and the standard cloud model, and normalizing the index evaluation cloud model corresponding to each target electric energy substitution technical evaluation index to obtain the subjective weight of each target electric energy substitution technical evaluation index.
In one embodiment, the determining the target fuzzy relation matrix corresponding to each target power substitution technical evaluation index and the comprehensive evaluation level includes:
constructing an evaluation domain according to each target electric energy substitution technical evaluation index and each target electric energy substitution technical evaluation object, and constructing a grade domain according to the comprehensive evaluation grade;
Establishing an initial fuzzy relation matrix between the evaluation domain and the grade domain;
and normalizing matrix elements in the initial fuzzy relation matrix by adopting the target electric energy substitution technology evaluation index to obtain the target fuzzy relation matrix.
In one embodiment, the step of normalizing matrix elements in the initial fuzzy relation matrix by using the target electrical energy substitution technology evaluation index to obtain the target fuzzy relation matrix includes:
normalizing matrix elements in the initial fuzzy relation matrix according to the following expression:
wherein i and j respectively represent an i-th item standard electric energy substitution technical evaluation index and a j-th item standard electric energy substitution technical evaluation index, r is a matrix element, and P ij The degree that the i-th item standard electric energy replacement technology evaluation index meets the j-th item standard electric energy replacement technology evaluation index, namely the membership degree, and n is the total number of the target electric energy replacement technology evaluation indexes.
In a second aspect, the present application provides an electrical energy substitution technology evaluation device based on a cloud model-entropy weighting method, the device including:
the target electric energy replacement technology evaluation index determining module is used for determining a plurality of target electric energy replacement technology evaluation indexes from a plurality of pre-acquired electric energy replacement technology evaluation indexes and determining a target electric energy replacement technology evaluation object and a comprehensive evaluation grade;
The fuzzy comprehensive evaluation model determining module is used for determining a fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technology evaluation index, wherein the fuzzy comprehensive evaluation model is formed by normalizing a target weight based on each target electric energy substitution technology evaluation index and a target fuzzy relation matrix corresponding to each target electric energy substitution technology evaluation index and the comprehensive evaluation grade, each target weight is an average value of a subjective weight and an objective weight of each target electric energy substitution technology evaluation index, the subjective weight is a comprehensive language evaluation cloud model corresponding to an evaluation language of each electric energy substitution technology evaluation index based on a plurality of experts, and an index evaluation cloud model corresponding to each electric energy substitution technology evaluation index, and the objective weight is obtained by calculating sample data of each target electric energy substitution technology evaluation index and each pre-obtained target electric energy substitution technology evaluation index by adopting an entropy weight method;
the evaluation score acquisition module is used for evaluating the target electric energy substitution technology evaluation object by adopting the fuzzy comprehensive evaluation model to obtain a target evaluation grade of the target electric energy substitution technology evaluation object;
And the evaluation result determining module is used for determining the evaluation score of the target electric energy substitution technology evaluation object according to the target evaluation grade and the comprehensive evaluation grade so as to analyze the evaluation result according to the evaluation score.
In a third aspect, the present application provides a storage medium having stored therein computer readable instructions, which when executed by one or more processors, cause the one or more processors to perform the steps of the power substitution technique evaluation method based on the cloud model-entropy weight method according to any one of the embodiments above.
In a fourth aspect, the present application provides a computer device comprising: one or more processors, and memory;
the memory stores computer readable instructions that, when executed by the one or more processors, perform the steps of the cloud model-entropy weight method-based power substitution technique evaluation method of any of the embodiments above.
From the above technical solutions, the embodiments of the present application have the following advantages:
in the electric energy substitution technology evaluation method and device based on the cloud model-entropy weight method, a plurality of target electric energy substitution technology evaluation indexes are determined in a plurality of pre-acquired electric energy substitution technology evaluation indexes, and a target electric energy substitution technology evaluation object and a comprehensive evaluation grade are determined; determining a fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technology evaluation index, wherein the fuzzy comprehensive evaluation model is constructed based on a target weight of each target electric energy substitution technology evaluation index and a target fuzzy relation matrix corresponding to each target electric energy substitution technology evaluation index and comprehensive evaluation grade, each target weight is an average value of subjective weight and objective weight of each target electric energy substitution technology evaluation index, the subjective weight is a comprehensive language evaluation cloud model corresponding to an evaluation language of each electric energy substitution technology evaluation index based on a plurality of experts, and an index evaluation cloud model corresponding to each electric energy substitution technology evaluation index, the objective weight is obtained by normalizing the index evaluation cloud model corresponding to each target electric energy substitution technology evaluation index, and sample data of each target electric energy substitution technology evaluation index obtained in advance are calculated by adopting an entropy weight method; evaluating the target electric energy substitution technology evaluation object by adopting a fuzzy comprehensive evaluation model to obtain a target evaluation grade of the target electric energy substitution technology evaluation object; and determining the evaluation score of the target electric energy substitution technology evaluation object according to the target evaluation grade and the comprehensive evaluation grade, so as to analyze the evaluation result according to the evaluation score. The cloud model-entropy weight method is adopted to determine the target weight of each target electric energy substitution technical evaluation index, subjective factors and objective factors can be considered at the same time, and the problem of subjective and objective unbalance in the evaluation process of the existing evaluation method is avoided to a certain extent. And evaluating the target electric energy substitution technology evaluation object by adopting a fuzzy comprehensive evaluation model, and converting the evaluation result into a score according to the comprehensive evaluation grade, thereby solving the problem that the existing evaluation result is difficult to quantify. Thus, a complete and scientific evaluation method and index system can be formed to evaluate the comprehensive benefit of the electric energy substitution technology.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive faculty for a person skilled in the art.
Fig. 1 is a flow chart of an electric energy substitution technology evaluation method based on a cloud model-entropy weight method according to an embodiment of the present application;
fig. 2 is a flowchart of a subjective weight step of determining an evaluation index of each target power substitution technique according to an embodiment of the present application;
FIG. 3 is a flowchart illustrating a step of determining a target fuzzy relation matrix corresponding to each target power substitution technical evaluation index and the comprehensive evaluation level according to the embodiment of the present application;
fig. 4 is a schematic structural diagram of an electrical energy substitution technology evaluation device based on a cloud model-entropy weight method according to an embodiment of the present application;
fig. 5 is a schematic diagram of an internal structure of a computer device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
The application provides an electric energy substitution technology evaluation method based on a cloud model-entropy weight method. The following embodiments will be described by taking the application of the method to a computer device as an example, and it will be understood that the computer device may be various devices with data processing functions, and may be, but not limited to, a single server, a server cluster, a personal notebook, a desktop computer, and the like. As shown in fig. 1, the present application provides a method for evaluating an electric energy substitution technology based on a cloud model-entropy weight method, which may include the following steps:
s101: a plurality of target electric energy substitution technology evaluation indexes are determined in a plurality of pre-acquired electric energy substitution technology evaluation indexes, and a target electric energy substitution technology evaluation object and a comprehensive evaluation grade are determined.
The electric energy replacing technology refers to technology for replacing the traditional electric energy supply or using mode by utilizing other energy sources or technologies, and aims to improve the energy utilization efficiency, reduce the energy consumption or improve the environmental impact. The electric energy substitution technique evaluation index refers to an index for evaluating and comparing the performances and effects of different electric energy substitution techniques. Electrical energy replacement technology evaluations may include, but are not limited to, energy efficiency improvement ratios, energy saving potential, carbon emission reduction, cost effectiveness, and sustainability. The electric energy replacement technology evaluation object refers to a specific electric energy replacement technology product, item or system. The electric energy replacement technology evaluation object may be a single device, an energy management system, and an energy supply scheme. The comprehensive evaluation grade refers to a grade set by comprehensively comparing and judging the electric energy substitution technology according to the evaluation index. The comprehensive evaluation level dividing criteria may be determined according to specific requirements, and may be, for example, a high level, a good level, a medium level, and a poor level, or may be evaluated using a score level system.
In this step, first, according to the purpose and the demand of the electric energy substitution technique evaluation, an index related to the purpose and the demand of the evaluation may be selected from a plurality of electric energy substitution technique evaluation indexes acquired in advance. While determining the electrical energy replacement technology object to be evaluated. In order to comprehensively compare and judge the evaluation results, the comprehensive evaluation level also needs to be determined.
S102: and determining a fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technology evaluation index.
The fuzzy comprehensive evaluation model is constructed based on a target weight of each target electric energy substitution technology evaluation index and a target fuzzy relation matrix corresponding to each target electric energy substitution technology evaluation index and the comprehensive evaluation grade, each target weight is an average value of a subjective weight and an objective weight of each target electric energy substitution technology evaluation index, the subjective weight is obtained by calculating sample data of each target electric energy substitution technology evaluation index and each target electric energy substitution technology evaluation index obtained by adopting an entropy weight method based on a comprehensive language evaluation cloud model corresponding to an evaluation language of each electric energy substitution technology evaluation index by a plurality of experts and an index evaluation cloud model corresponding to each electric energy substitution technology evaluation index, and the objective weight is obtained by normalizing the index evaluation cloud model corresponding to each target electric energy substitution technology evaluation index.
In the step, the average value of the subjective weight and the objective weight of each target electric energy substitution technology evaluation index is calculated as the target weight. The subjective weight can be obtained by constructing a comprehensive language evaluation cloud model through expert on the evaluation language of the evaluation index. The objective weight can be obtained by calculating each target electric energy substitution technical evaluation index and pre-acquired sample data by adopting an entropy weight method. And constructing a target fuzzy relation matrix according to the fuzzy relation between the technical evaluation index and the comprehensive evaluation level of each target electric energy substitution. In one embodiment, the fuzzy relation between the evaluation index and the comprehensive evaluation grade can be evaluated and judged by an expert. And combining the target weight and the target fuzzy relation matrix to obtain a fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technology evaluation index.
It can be understood that the entropy weight method is a commonly used multi-index decision method for calculating the weight of each index in the decision process, and the basic idea is to measure the information quantity inside the index and the difference between the indexes through the concept of information entropy, so as to determine the relative importance degree of each index in the decision.
S103: and evaluating the target electric energy substitution technology evaluation object by adopting the fuzzy comprehensive evaluation model to obtain a target evaluation grade of the target electric energy substitution technology evaluation object.
In the step, the comprehensive evaluation grade and each target electric energy substitution technology evaluation index are combined in the fuzzy comprehensive evaluation model, so that the fuzzy comprehensive evaluation model is adopted to evaluate the target electric energy substitution technology evaluation object, and the target evaluation grade of the target electric energy substitution technology evaluation object can be obtained.
S104: and determining the evaluation value of the target electric energy substitution technology evaluation object according to the target evaluation grade and the comprehensive evaluation grade, so as to analyze the evaluation result according to the evaluation value.
In this step, the relationship between each evaluation level and the evaluation score in the comprehensive evaluation level may be determined first, and then, according to the target evaluation level, the evaluation score corresponding to the target evaluation level is determined from the relationship between each evaluation level and the evaluation score, that is, the evaluation score of the target electrical energy replacement technology evaluation object is determined, so as to quantify the evaluation result of the target electrical energy replacement technology evaluation object, thereby better analyzing the evaluation result.
In one example, a range of evaluation scores corresponding to each of the comprehensive evaluation levels is first determined. For example, a class A corresponding score of 90, a class B corresponding score of 80, and so on are set. And converting the target evaluation grade into a corresponding evaluation score according to the target evaluation grade and the set corresponding relation. For example, if the target rating is B-level, the corresponding rating score may be 80. The performance of the target electric energy substitution technology evaluation object in the whole evaluation can be judged according to the evaluation score. Meanwhile, according to different comprehensive evaluation grades, the evaluation objects with different grades can be compared and classified.
In the above embodiment, a plurality of target electric energy replacement technology evaluation indexes are determined among a plurality of electric energy replacement technology evaluation indexes acquired in advance, and a target electric energy replacement technology evaluation object and a comprehensive evaluation level are determined; determining a fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technology evaluation index, wherein the fuzzy comprehensive evaluation model is constructed based on a target weight of each target electric energy substitution technology evaluation index and a target fuzzy relation matrix corresponding to each target electric energy substitution technology evaluation index and comprehensive evaluation grade, each target weight is an average value of subjective weight and objective weight of each target electric energy substitution technology evaluation index, the subjective weight is a comprehensive language evaluation cloud model corresponding to an evaluation language of each electric energy substitution technology evaluation index based on a plurality of experts, and an index evaluation cloud model corresponding to each electric energy substitution technology evaluation index, the objective weight is obtained by normalizing the index evaluation cloud model corresponding to each target electric energy substitution technology evaluation index, and sample data of each target electric energy substitution technology evaluation index obtained in advance are calculated by adopting an entropy weight method; evaluating the target electric energy substitution technology evaluation object by adopting a fuzzy comprehensive evaluation model to obtain a target evaluation grade of the target electric energy substitution technology evaluation object; and determining the evaluation score of the target electric energy substitution technology evaluation object according to the target evaluation grade and the comprehensive evaluation grade, so as to analyze the evaluation result according to the evaluation score. The cloud model-entropy weight method is adopted to determine the target weight of each target electric energy substitution technical evaluation index, subjective factors and objective factors can be considered at the same time, and the problem of subjective and objective unbalance in the evaluation process of the existing evaluation method is avoided to a certain extent. And evaluating the target electric energy substitution technology evaluation object by adopting a fuzzy comprehensive evaluation model, and converting the evaluation result into a score according to the comprehensive evaluation grade, thereby solving the problem that the existing evaluation result is difficult to quantify. Thus, a complete and scientific evaluation method and index system can be formed to evaluate the comprehensive benefit of the electric energy substitution technology.
In one embodiment, the construction process of the fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technical evaluation index includes:
converting the target weight of each target electric energy substitution technical evaluation index into a fuzzy weight vector;
and synthesizing the fuzzy weight vector and the target fuzzy relation matrix to obtain the fuzzy comprehensive evaluation model.
Specifically, the weight value of each evaluation index can be mapped to the corresponding fuzzy set degree to obtain the fuzzy weight vector corresponding to each evaluation index. The target fuzzy relation matrix reflects fuzzy membership between the electric energy substitution technology evaluation index and each evaluation grade in the comprehensive evaluation grades. And synthesizing the fuzzy weight vector and the target fuzzy relation matrix to obtain a fuzzy comprehensive evaluation model. In one embodiment, a fuzzy aggregation operation method, such as a fuzzy weighted average method or a fuzzy multiplication operation, may be used, in a specific operation, each dimension of the fuzzy weight vector may be corresponding to a corresponding row of the target fuzzy relation matrix, and a fuzzy numerical value of the composite result may be obtained according to the fuzzy aggregation operation rule. Wherein the target weight of each target electric energy substitution technical evaluation index is equal to or greater than 0, and the sum of the target weights of the target electric energy substitution technical evaluation indexes is equal to 1.
In one example, the fuzzy comprehensive evaluation model is obtained according to the following expression:
wherein B is a fuzzy comprehensive evaluation model, A is a fuzzy weight vector, R is a target fuzzy relation matrix, a m Target weight r for evaluating index of mth target electric energy substitution technology nm For matrix elements of the target fuzzy relation matrix, the operator is an algorithm which must conform to fuzzy mathematics for fuzzy evaluation operation.
In this embodiment, the fuzzy comprehensive evaluation model can consider a plurality of evaluation indexes at the same time, and integrate the weights of the indexes, thereby evaluating the performance and effect of the target electric energy substitution technology more comprehensively.
As shown in fig. 2, in one embodiment, the determining the subjective weight of each target power replacement technology evaluation index includes:
s201: acquiring the evaluation languages of each expert on each electric energy substitution technology evaluation index, and determining a language evaluation cloud model corresponding to the evaluation language of each expert on each electric energy substitution technology evaluation index;
s202: synthesizing each language evaluation cloud model to obtain the comprehensive language evaluation cloud model;
s203: calculating an index evaluation cloud model corresponding to each electric energy substitution technical evaluation index according to a language evaluation cloud model corresponding to the evaluation language of each electric energy substitution technical evaluation index by each expert;
S204: and normalizing the index evaluation cloud model corresponding to each target electric energy substitution technology evaluation index based on the comprehensive language evaluation cloud model and each index evaluation cloud model to obtain the subjective weight of each target electric energy substitution technology evaluation index.
Specifically, first, it is necessary to acquire an evaluation language, such as excellent, good, general, poor, and very poor, for each power substitution technique evaluation index, by the experts. The evaluation language may represent the performance and level of the power replacement technology evaluation index in various aspects, and different experts may give different evaluation languages to the same power replacement technology evaluation index due to different subjective understanding and experience of each expert. Aiming at different evaluation languages of different experts, the language evaluation cloud model corresponding to the expert evaluation language can be calculated to convert the different evaluation languages. According to the language evaluation cloud model of different experts, the language evaluation cloud models can be combined into a comprehensive language evaluation cloud model by using a synthesis algorithm, and for example, a hierarchical analysis method, fuzzy comprehensive evaluation and the like can be adopted. Thus, the opinion of all the experts can be comprehensively considered, and the inconsistency of the evaluation results caused by individual deviation can be reduced. Based on the language evaluation cloud model corresponding to the evaluation language provided by each expert, an index evaluation cloud model corresponding to each evaluation index can be calculated. And finally, carrying out normalization processing on the comprehensive language evaluation cloud model and the index evaluation cloud model according to the comprehensive language evaluation cloud model and each index evaluation cloud model, so as to obtain the subjective weight of each evaluation index.
In one example, let the power replacement technique evaluation index be C j (j=1, 2,3, …, n), by S-bit expert S k Importance of expert group consisting of (k=1, 2,3, …, s) on each electric energy substitution technology evaluation indexPerforming language evaluation, and converting the evaluation language into a corresponding cloud modelThe evaluation clouds given by different experts were synthesized according to the following expression:
wherein a, b and h are constants and represent weights of the belonging items, (E) xj ,E nj ,H ej ) Representing all experts for electric energy substitution technical evaluation index C j A language evaluation cloud model corresponding to the evaluation language is made, n represents the total number of the evaluation indexes of the electric energy substitution technology, and C j Represents the j-th electric energy substitution technical evaluation index, S represents the total number of experts, S k Representing the expert in the k-th position,a language evaluation cloud model corresponding to an evaluation language representing the evaluation index of the kth expert on the jth electric energy substitution technology,>representing the desired value->Representing entropy->Representing the super entropy.
In this embodiment, subjective opinion of each expert can be fully considered by acquiring the evaluation language of each expert for each evaluation index; the cloud model is evaluated by integrating a plurality of indexes, so that the interaction and importance among different indexes can be considered, the unilateral performance of single index evaluation is solved, and a more comprehensive and comprehensive evaluation result is provided; through normalization processing, subjective weights of all indexes can be mapped into a unified interval, so that the weights have comparability, and comprehensive evaluation and decision making are facilitated.
In one embodiment, the step of calculating, according to a language evaluation cloud model corresponding to an evaluation language of each of the power substitution technical evaluation indexes by each of the experts, an index evaluation cloud model corresponding to each of the power substitution technical evaluation indexes includes:
calculating an index evaluation cloud model corresponding to each electric energy substitution technology evaluation index according to the following expression:
wherein Z is j An index evaluation cloud model for the j-th electric energy substitution technical evaluation index, s is the total number of experts, k is the k-th expert,and a language evaluation language model corresponding to the evaluation language of the j-th electric energy substitution technology evaluation index is provided for the k-th expert.
In this embodiment, by averaging the evaluation results of different experts, the opinion of multiple experts can be synthesized to obtain a more comprehensive and accurate evaluation result, which is helpful for reducing the deviation and subjectivity of the opinion of a single expert.
In one embodiment, the step of normalizing the index evaluation cloud model corresponding to each target electrical energy substitution technical evaluation index based on the comprehensive language evaluation cloud model and each index evaluation cloud model to obtain subjective weight of each target electrical energy substitution technical evaluation index includes:
Determining a standard evaluation cloud model in the comprehensive language evaluation cloud model and each index evaluation cloud model;
calculating the similarity between the index evaluation cloud model corresponding to each target electric energy substitution technical evaluation index and the standard cloud model, and normalizing the index evaluation cloud model corresponding to each target electric energy substitution technical evaluation index to obtain the subjective weight of each target electric energy substitution technical evaluation index.
Specifically, the cloud model with the highest evaluation among the comprehensive language evaluation cloud model and the individual index evaluation cloud models may be selected as the standard cloud model with the importance of 1. And comparing the index evaluation cloud model corresponding to each target electric energy substitution technical evaluation index with the standard cloud model, and calculating the similarity between the index evaluation cloud model and the standard cloud model. In one embodiment, a euclidean distance or other similarity index between two cloud models may be calculated, and the similarity between the two cloud models determined. And carrying out normalization processing on the index evaluation cloud model corresponding to each target electric energy substitution technical evaluation index according to the similarity calculation result to obtain the subjective weight of each target electric energy substitution technical evaluation index. In one embodiment, a linear or nonlinear normalization function may be used to map similarity between 0 and 1, resulting in subjective weights.
In one example, a standard cloud model Z is first determined * Calculating an index evaluation cloud model Z corresponding to each target electric energy substitution technology evaluation index j And normalized, can be calculated using the following expression:
wherein r is j Representing the subjective weight of the j-th target power replacement technique evaluation index, sim () is a function for measuring the similarity between two vectors, and n is the total number of target power replacement technique evaluation indexes.
In this embodiment, the similarity between the index evaluation cloud model corresponding to each target electric energy substitution technology evaluation index and the standard cloud model can be evaluated by comparing the index evaluation cloud model with the standard evaluation cloud model, so that the performance and the gap of the index evaluation cloud model corresponding to each target electric energy substitution technology evaluation index under actual conditions are known, the relevance and the mutual influence among the indexes can be found, and the one-sided and isolated evaluation results can be avoided. Through normalization processing, the similarity of each index evaluation cloud model is mapped to a unified interval to obtain subjective weights, so that the weights of different indexes can be compared and ordered, and a decision maker is facilitated to more scientifically and comprehensively consider the importance of each index when preparing an evaluation index system.
As shown in fig. 3, in one embodiment, the determining process of the target fuzzy relation matrix corresponding to each of the target power substitution technology evaluation indexes and the comprehensive evaluation level includes:
s301: constructing an evaluation domain according to each target electric energy substitution technical evaluation index and each target electric energy substitution technical evaluation object, and constructing a grade domain according to the comprehensive evaluation grade;
s302: establishing an initial fuzzy relation matrix between the evaluation domain and the grade domain;
s303: and normalizing matrix elements in the initial fuzzy relation matrix by adopting the target electric energy substitution technology evaluation index to obtain the target fuzzy relation matrix.
Specifically, an evaluation domain is determined according to the target electric energy substitution technology evaluation index and the evaluation object, and meanwhile, a grade domain is constructed according to the division standard of the comprehensive evaluation grade. When the initial fuzzy relation matrix is established, the value of the evaluation domain is mapped to the grade in the grade domain. And normalizing the elements in the initial fuzzy relation matrix by using the target electric energy to replace the technical evaluation index. In one embodiment, the normalization process may employ a mathematical function or expert experience with defined rules.
In one embodiment, the step of normalizing matrix elements in the initial fuzzy relation matrix by the target power substitution technique evaluation index to obtain the target fuzzy relation matrix includes:
normalizing matrix elements in the initial fuzzy relation matrix according to the following expression:
wherein i and j respectively represent an i-th item standard electric energy substitution technical evaluation index and a j-th item standard electric energy substitution technical evaluation index, r is a matrix element, and P ij The degree that the i-th item standard electric energy replacement technology evaluation index meets the j-th item standard electric energy replacement technology evaluation index, namely the membership degree, and n is the total number of the target electric energy replacement technology evaluation indexes.
The electric energy substitution technology evaluation device based on the cloud model-entropy weight method provided by the embodiment of the application is described below, and the electric energy substitution technology evaluation device based on the cloud model-entropy weight method described below and the electric energy substitution technology evaluation method based on the cloud model-entropy weight method described above can be correspondingly referred to each other. As shown in fig. 4, the electric energy substitution technology evaluation device based on the cloud model-entropy weight method provided by the application may include the following structures:
The target electric energy substitution technology evaluation index determining module 401 is configured to determine a plurality of target electric energy substitution technology evaluation indexes from a plurality of pre-acquired electric energy substitution technology evaluation indexes, and determine a target electric energy substitution technology evaluation object and a comprehensive evaluation level;
a fuzzy comprehensive evaluation model determining module 402, configured to determine a fuzzy comprehensive evaluation model corresponding to each target electrical energy substitution technical evaluation index, where the fuzzy comprehensive evaluation model is based on a target weight of each target electrical energy substitution technical evaluation index and a target fuzzy relation matrix corresponding to each target electrical energy substitution technical evaluation index and the comprehensive evaluation level, each target weight is constructed by an average value of a subjective weight and an objective weight of each target electrical energy substitution technical evaluation index, the subjective weight is based on a comprehensive language evaluation cloud model corresponding to an evaluation language of each electrical energy substitution technical evaluation index by a plurality of experts, and an index evaluation cloud model corresponding to each electrical energy substitution technical evaluation index, and the objective weight is obtained by normalizing an index evaluation cloud model corresponding to each target electrical energy substitution technical evaluation index, and sample data of each target electrical energy substitution technical evaluation index obtained in advance by an entropy weight method;
The evaluation score obtaining module 403 is configured to evaluate the target electrical energy substitution technology evaluation object by using the fuzzy comprehensive evaluation model, so as to obtain a target evaluation grade of the target electrical energy substitution technology evaluation object;
and an evaluation result determining module 404, configured to determine an evaluation score of the target electric energy replacement technology evaluation object according to the target evaluation grade and the comprehensive evaluation grade, so as to analyze an evaluation result according to the evaluation score.
In one embodiment, the fuzzy synthetic valuation model determination module 402 includes:
the fuzzy weight vector determining submodule is used for converting the target weight of each target electric energy substitution technical evaluation index into a fuzzy weight vector;
and the fuzzy comprehensive evaluation model determining submodule is used for synthesizing the fuzzy weight vector and the target fuzzy relation matrix to obtain the fuzzy comprehensive evaluation model.
In one embodiment, the fuzzy synthetic valuation model determination module 402 includes:
the language evaluation cloud model determining submodule is used for obtaining the evaluation language of each expert on each electric energy substitution technical evaluation index and determining a language evaluation cloud model corresponding to the evaluation language of each expert on each electric energy substitution technical evaluation index;
The comprehensive language evaluation cloud model determining submodule is used for synthesizing each language evaluation cloud model to obtain the comprehensive language evaluation cloud model;
the index evaluation cloud model determination submodule is used for calculating an index evaluation cloud model corresponding to each electric energy substitution technical evaluation index according to a language evaluation cloud model corresponding to the evaluation language of each electric energy substitution technical evaluation index by each expert;
and the subjective weight determining sub-module is used for normalizing the index evaluation cloud model corresponding to each target electric energy substitution technology evaluation index based on the comprehensive language evaluation cloud model and each index evaluation cloud model to obtain the subjective weight of each target electric energy substitution technology evaluation index.
In one embodiment, the index evaluation cloud model determination submodule includes:
the index evaluation cloud model calculation unit is used for calculating an index evaluation cloud model corresponding to each electric energy substitution technology evaluation index according to the following expression:
wherein Z is j An index evaluation cloud model for the j-th electric energy substitution technical evaluation index, s is the total number of experts, k is the k-th expert,and a language evaluation language model corresponding to the evaluation language of the j-th electric energy substitution technology evaluation index is provided for the k-th expert.
In one embodiment, the subjective weight determination submodule includes:
the standard evaluation cloud model determining unit is used for determining a standard evaluation cloud model in the comprehensive language evaluation cloud model and each index evaluation cloud model;
and the subjective weight determining unit is used for calculating the similarity between the index evaluation cloud model corresponding to each target electric energy substitution technical evaluation index and the standard cloud model, and normalizing the index evaluation cloud model corresponding to each target electric energy substitution technical evaluation index to obtain the subjective weight of each target electric energy substitution technical evaluation index.
In one embodiment, the fuzzy synthetic valuation model determination module 402 includes:
an evaluation domain construction sub-module, configured to construct an evaluation domain according to each of the target electric energy replacement technology evaluation index and the target electric energy replacement technology evaluation object, and construct a grade domain according to the comprehensive evaluation grade;
an initial fuzzy relation matrix establishing sub-module, which is used for establishing an initial fuzzy relation matrix between the evaluation domain and the grade domain;
and the target fuzzy relation matrix determining submodule is used for normalizing matrix elements in the initial fuzzy relation matrix by adopting the target electric energy substitution technology evaluation index to obtain the target fuzzy relation matrix.
In one embodiment, the target fuzzy relation matrix determination submodule includes:
a normalization calculation unit, configured to normalize matrix elements in the initial fuzzy relation matrix according to the following expression:
wherein i and j respectively represent an i-th item standard electric energy substitution technical evaluation index and a j-th item standard electric energy substitution technical evaluation index, r is a matrix element, and P ij The degree that the i-th item standard electric energy replacement technology evaluation index meets the j-th item standard electric energy replacement technology evaluation index, namely the membership degree, and n is the total number of the target electric energy replacement technology evaluation indexes.
In one embodiment, the present application further provides a storage medium having stored therein computer readable instructions, which when executed by one or more processors, cause the one or more processors to perform the steps of the cloud model-entropy weight method-based power substitution technique evaluation method as set forth in any one of the above embodiments.
In one embodiment, the present application further provides a computer device having stored therein computer readable instructions that, when executed by one or more processors, cause the one or more processors to perform the steps of the cloud model-entropy weight method-based power substitution technique evaluation method as in any of the above embodiments.
Schematically, as shown in fig. 5, fig. 5 is a schematic internal structure of a computer device according to an embodiment of the present application, and the computer device 500 may be provided as a server. Referring to FIG. 5, a computer device 500 includes a processing component 502 that further includes one or more processors and memory resources represented by memory 501 for storing instructions, such as applications, executable by the processing component 502. The application program stored in the memory 501 may include one or more modules each corresponding to a set of instructions. Further, the processing component 502 is configured to execute instructions to perform the power replacement technique evaluation method based on the cloud model-entropy weight method of any of the embodiments described above.
The computer device 500 may also include a power supply component 503 configured to perform power management of the computer device 500, a wired or wireless network interface 504 configured to connect the computer device 500 to a network, and an input output (I/O) interface 505. The computer device 500 may operate based on an operating system stored in memory 501, such as Windows Server TM, mac OS XTM, unix TM, linux TM, free BSDTM, or the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 5 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element. Herein, "a," "an," "the," and "the" may also include plural forms, unless the context clearly indicates otherwise. Plural means at least two cases such as 2, 3, 5 or 8, etc. "and/or" includes any and all combinations of the associated listed items.
In the present specification, each embodiment is described in a progressive manner, and each embodiment focuses on the difference from other embodiments, and may be combined according to needs, and the same similar parts may be referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. An electric energy substitution technology evaluation method based on a cloud model-entropy weight method is characterized by comprising the following steps:
determining a plurality of target electric energy substitution technical evaluation indexes from a plurality of pre-acquired electric energy substitution technical evaluation indexes, and determining target electric energy substitution technical evaluation objects and comprehensive evaluation grades;
determining a fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technology evaluation index, wherein the fuzzy comprehensive evaluation model is constructed based on target weights of each target electric energy substitution technology evaluation index and a target fuzzy relation matrix corresponding to each target electric energy substitution technology evaluation index and the comprehensive evaluation grade, each target weight is an average value of subjective weights and objective weights of each target electric energy substitution technology evaluation index, the subjective weights are comprehensive language evaluation cloud models corresponding to evaluation languages of each electric energy substitution technology evaluation index based on a plurality of experts, and index evaluation cloud models corresponding to each electric energy substitution technology evaluation index, the objective weights are obtained by normalizing the index evaluation cloud models corresponding to each target electric energy substitution technology evaluation index by adopting an entropy weight method, and sample data of each target electric energy substitution technology evaluation index obtained in advance;
Evaluating the target electric energy substitution technology evaluation object by adopting the fuzzy comprehensive evaluation model to obtain a target evaluation grade of the target electric energy substitution technology evaluation object;
and determining the evaluation value of the target electric energy substitution technology evaluation object according to the target evaluation grade and the comprehensive evaluation grade, so as to analyze the evaluation result according to the evaluation value.
2. The electric energy substitution technique evaluation method based on the cloud model-entropy weight method according to claim 1, wherein the construction process of the fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technique evaluation index comprises the steps of:
converting the target weight of each target electric energy substitution technical evaluation index into a fuzzy weight vector;
and synthesizing the fuzzy weight vector and the target fuzzy relation matrix to obtain the fuzzy comprehensive evaluation model.
3. The electric energy substitution technique evaluation method based on the cloud model-entropy weight method according to claim 1, wherein the determination process of subjective weight of each target electric energy substitution technique evaluation index comprises:
acquiring the evaluation languages of each expert on each electric energy substitution technology evaluation index, and determining a language evaluation cloud model corresponding to the evaluation language of each expert on each electric energy substitution technology evaluation index;
Synthesizing each language evaluation cloud model to obtain the comprehensive language evaluation cloud model;
calculating an index evaluation cloud model corresponding to each electric energy substitution technical evaluation index according to a language evaluation cloud model corresponding to the evaluation language of each electric energy substitution technical evaluation index by each expert;
and normalizing the index evaluation cloud model corresponding to each target electric energy substitution technology evaluation index based on the comprehensive language evaluation cloud model and each index evaluation cloud model to obtain the subjective weight of each target electric energy substitution technology evaluation index.
4. The method for evaluating an electric energy substitution technique based on a cloud model-entropy weight method according to claim 3, wherein the step of calculating an index evaluation cloud model corresponding to each electric energy substitution technique evaluation index according to a language evaluation cloud model corresponding to an evaluation language of each electric energy substitution technique evaluation index by each expert comprises:
calculating an index evaluation cloud model corresponding to each electric energy substitution technology evaluation index according to the following expression:
wherein Z is j An index evaluation cloud model for the j-th electric energy substitution technical evaluation index, s is the total number of experts, k is the k-th expert, And a language evaluation language model corresponding to the evaluation language of the j-th electric energy substitution technology evaluation index is provided for the k-th expert.
5. The method for evaluating an electric energy substitution technique based on a cloud model-entropy weight method according to claim 3, wherein the step of normalizing the index evaluation cloud model corresponding to each target electric energy substitution technique evaluation index based on the comprehensive language evaluation cloud model and each index evaluation cloud model to obtain subjective weight of each target electric energy substitution technique evaluation index comprises the steps of:
determining a standard evaluation cloud model in the comprehensive language evaluation cloud model and each index evaluation cloud model;
calculating the similarity between the index evaluation cloud model corresponding to each target electric energy substitution technical evaluation index and the standard cloud model, and normalizing the index evaluation cloud model corresponding to each target electric energy substitution technical evaluation index to obtain the subjective weight of each target electric energy substitution technical evaluation index.
6. The electric energy substitution technique evaluation method based on the cloud model-entropy weight method according to claim 1, wherein the determination process of the target fuzzy relation matrix corresponding to each of the target electric energy substitution technique evaluation index and the comprehensive evaluation level includes:
Constructing an evaluation domain according to each target electric energy substitution technical evaluation index and each target electric energy substitution technical evaluation object, and constructing a grade domain according to the comprehensive evaluation grade;
establishing an initial fuzzy relation matrix between the evaluation domain and the grade domain;
and normalizing matrix elements in the initial fuzzy relation matrix by adopting the target electric energy substitution technology evaluation index to obtain the target fuzzy relation matrix.
7. The method for evaluating an electric energy substitution technique based on a cloud model-entropy weight method according to claim 6, wherein the step of normalizing matrix elements in the initial fuzzy relation matrix by using the target electric energy substitution technique evaluation index to obtain the target fuzzy relation matrix comprises the steps of:
normalizing matrix elements in the initial fuzzy relation matrix according to the following expression:
wherein i and j respectively represent an i-th item standard electric energy substitution technical evaluation index and a j-th item standard electric energy substitution technical evaluation index, r is a matrix element, and P ij The degree that the i-th item standard electric energy replacement technology evaluation index meets the j-th item standard electric energy replacement technology evaluation index, namely the membership degree, and n is the total number of the target electric energy replacement technology evaluation indexes.
8. An electric energy substitution technology evaluation device based on a cloud model-entropy weight method, which is characterized by comprising:
the target electric energy replacement technology evaluation index determining module is used for determining a plurality of target electric energy replacement technology evaluation indexes from a plurality of pre-acquired electric energy replacement technology evaluation indexes and determining a target electric energy replacement technology evaluation object and a comprehensive evaluation grade;
the fuzzy comprehensive evaluation model determining module is used for determining a fuzzy comprehensive evaluation model corresponding to each target electric energy substitution technology evaluation index, wherein the fuzzy comprehensive evaluation model is formed by normalizing a target weight based on each target electric energy substitution technology evaluation index and a target fuzzy relation matrix corresponding to each target electric energy substitution technology evaluation index and the comprehensive evaluation grade, each target weight is an average value of a subjective weight and an objective weight of each target electric energy substitution technology evaluation index, the subjective weight is a comprehensive language evaluation cloud model corresponding to an evaluation language of each electric energy substitution technology evaluation index based on a plurality of experts, and an index evaluation cloud model corresponding to each electric energy substitution technology evaluation index, and the objective weight is obtained by calculating sample data of each target electric energy substitution technology evaluation index and each pre-obtained target electric energy substitution technology evaluation index by adopting an entropy weight method;
The evaluation score acquisition module is used for evaluating the target electric energy substitution technology evaluation object by adopting the fuzzy comprehensive evaluation model to obtain a target evaluation grade of the target electric energy substitution technology evaluation object;
and the evaluation result determining module is used for determining the evaluation score of the target electric energy substitution technology evaluation object according to the target evaluation grade and the comprehensive evaluation grade so as to analyze the evaluation result according to the evaluation score.
9. A storage medium, characterized by: the storage medium has stored therein computer readable instructions which, when executed by one or more processors, cause the one or more processors to perform the steps of the cloud model-entropy weight method-based power substitution technique evaluation method according to any one of claims 1 to 7.
10. A computer device, comprising: one or more processors, and memory;
stored in the memory are computer readable instructions which, when executed by the one or more processors, perform the steps of the cloud model-entropy weight method-based power substitution technique evaluation method of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311417448.9A CN117350594A (en) | 2023-10-27 | 2023-10-27 | Electric energy substitution technology evaluation method and device based on cloud model-entropy weight method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311417448.9A CN117350594A (en) | 2023-10-27 | 2023-10-27 | Electric energy substitution technology evaluation method and device based on cloud model-entropy weight method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117350594A true CN117350594A (en) | 2024-01-05 |
Family
ID=89357325
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311417448.9A Pending CN117350594A (en) | 2023-10-27 | 2023-10-27 | Electric energy substitution technology evaluation method and device based on cloud model-entropy weight method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117350594A (en) |
-
2023
- 2023-10-27 CN CN202311417448.9A patent/CN117350594A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Guo et al. | Decomposition weights and overall efficiency in two-stage additive network DEA | |
| Fan et al. | Technological innovation, trade openness, CO2 emission and economic growth: comparative analysis between China and India | |
| CN106845717B (en) | Energy efficiency evaluation method based on multi-model fusion strategy | |
| Chai et al. | A decomposition–integration model with dynamic fuzzy reconstruction for crude oil price prediction and the implications for sustainable development | |
| Malakouti et al. | Predicting wind power generation using machine learning and CNN-LSTM approaches | |
| Zamar et al. | A quantile-based scenario analysis approach to biomass supply chain optimization under uncertainty | |
| Hsin et al. | Application of game theory on parameter optimization of the novel two-stage Nash nonlinear grey Bernoulli model | |
| CN106056235A (en) | Power transmission grid efficiency and benefit detection method based on Klee method and matter element extension model | |
| Li et al. | Grey relational decision making model of three-parameter interval grey number based on AHP and DEA | |
| CN116169670A (en) | Short-term non-resident load prediction method and system based on improved neural network | |
| CN116823008A (en) | Park energy utilization efficiency evaluation method, system, equipment and storage medium | |
| Przymus et al. | Improving multivariate time series forecasting with random walks with restarts on causality graphs | |
| CN110458479A (en) | Potential evaluation method for converting technical achievements in new energy field into technical standards | |
| CN117474173B (en) | Multi-water source dynamic allocation device and system for plain river network area | |
| Bai | Key factor mining method of distribution network equipment operational efficiency based on Apriori and CNN | |
| Putra et al. | Modeling of high uncertainty photovoltaic generation in quasi dynamic power flow on distribution systems: A case study in Java Island, Indonesia | |
| CN117036781A (en) | Image classification method based on tree comprehensive diversity depth forests | |
| CN117350594A (en) | Electric energy substitution technology evaluation method and device based on cloud model-entropy weight method | |
| CN116613732A (en) | Multi-element load prediction method and system based on SHAP value selection strategy | |
| CN116108963A (en) | Electric power carbon emission prediction method and equipment based on integrated learning module | |
| Serna et al. | Multi-Criteria Decision-Making for Renewable Hydrogen Production Site Selection: a Systematic Literature Review | |
| Shokr et al. | A common weight data envelopment analysis approach for material selection | |
| CN114169226A (en) | Short-term power load prediction method, computer device, and storage medium | |
| Sujjaviriyasup et al. | A comparison between MODWT-SVM-DE hybrid model and ARIMA model in forecasting primary energy consumptions | |
| CN112036713A (en) | Coal-to-electricity comprehensive benefit evaluation method and system based on principal component analysis |
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 |