CN110264030A - A kind of new and old kinetic energy conversion effect evaluation method and system - Google Patents
A kind of new and old kinetic energy conversion effect evaluation method and system Download PDFInfo
- Publication number
- CN110264030A CN110264030A CN201910365737.6A CN201910365737A CN110264030A CN 110264030 A CN110264030 A CN 110264030A CN 201910365737 A CN201910365737 A CN 201910365737A CN 110264030 A CN110264030 A CN 110264030A
- Authority
- CN
- China
- Prior art keywords
- index
- new
- kinetic energy
- optimal
- fuzzy
- 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
- 230000000694 effects Effects 0.000 title claims abstract description 84
- 238000006243 chemical reaction Methods 0.000 title claims abstract description 72
- 238000011156 evaluation Methods 0.000 title claims abstract description 42
- 239000013598 vector Substances 0.000 claims abstract description 122
- 230000007306 turnover Effects 0.000 claims abstract description 62
- 238000000034 method Methods 0.000 claims abstract description 56
- 238000004458 analytical method Methods 0.000 claims abstract description 16
- 238000005265 energy consumption Methods 0.000 claims description 7
- 230000005611 electricity Effects 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 4
- 238000007619 statistical method Methods 0.000 claims description 4
- 230000004927 fusion Effects 0.000 claims description 3
- 238000006467 substitution reaction Methods 0.000 claims description 3
- 238000005303 weighing Methods 0.000 claims 2
- 230000008569 process Effects 0.000 description 11
- 238000010276 construction Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 235000013399 edible fruits Nutrition 0.000 description 3
- 238000012795 verification Methods 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 238000005457 optimization Methods 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000032696 parturition Effects 0.000 description 1
- 238000012797 qualification Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000001568 sexual effect Effects 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
- 230000009466 transformation 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
- 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
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
This application discloses a kind of new and old kinetic energy conversion effect evaluation method and systems, this method comprises: establishing new and old kinetic energy conversion effect assessment indicator system, the index in new and old kinetic energy conversion effect assessment indicator system includes the new and old kinetic energy turnover of level-one and the new and old kinetic energy turnover of second level；According to different stage, it is utilized respectively Fuzzy B WM method and Index Weights is carried out to the index, determine the weight of any index；According to the weight of different stage index, gray relative analysis method in the way of merging difference and except in the way of evaluates new and old kinetic energy conversion effect, obtains evaluation result.The system includes: that index system establishes module, Index Weights module and overall merit module.By the application, subjectivity of expert during judging that vector is constituted can be avoided, from shape and apart from upper definition synthetical grey relation degree, be conducive to the accuracy and reliability for improving new and old kinetic energy conversion effect assessment.
Description
Technical field
This application involves new and old kinetic energy switch technology fields, convert effect evaluation method more particularly to a kind of new and old kinetic energy
And system.
Background technique
New and old kinetic energy conversion is the grand strategy behave that I crosses Economic Development Mode Conversion, improve economic development quality.Such as
The new and old kinetic energy conversion of what research, and how progress effect is converted to new and old kinetic energy and evaluate, to preferably push new and old
The development of kinetic energy conversion is a major issue.
Current new and old kinetic energy study on the transformation is primarily upon the related notion of new and old kinetic energy conversion, realization means, Yi Jixin
Old kinetic energy conversion and the relationship between macroeconomy, the industrial structure, the not systematic effect assessment to the conversion of new and old kinetic energy
Method, it is especially considerably less to Effect study of the power industry in the conversion of new and old kinetic energy.At present to new and old kinetic energy conversion at
Effect evaluation, is usually artificially evaluated according to the effect that new and old kinetic energy is converted.
However, too strong due to artificially evaluating subjectivity, evaluation is tied at present in the effect assessment method of new and old kinetic energy conversion
Fruit is very inaccurate and unreliable, can not preferably push the development of new and old kinetic energy conversion.
Summary of the invention
This application provides a kind of new and old kinetic energy conversion effect evaluation method and systems, new and old dynamic in the prior art to solve
Effect assessment inaccuracy and insecure problem can be converted.
In order to solve the above-mentioned technical problem, the embodiment of the present application discloses following technical solution:
A kind of new and old kinetic energy conversion effect evaluation method, which comprises
New and old kinetic energy conversion effect assessment indicator system is established, the new and old kinetic energy is converted in effect assessment indicator system
Index includes the new and old kinetic energy turnover of level-one and the new and old kinetic energy turnover of second level, the new and old kinetic energy turnover packet of level-one
Include: economic indicator, power consumption index and energy efficiency indexes, the new and old kinetic energy turnover of second level are the new and old kinetic energy conversion of the level-one
Index under index；
According to different stage, it is utilized respectively Fuzzy B WM (Best and Worst Method, optimal most bad method) method pair
The index carries out Index Weights, determines the weight of any index；
According to the weight of different stage index, gray relative analysis method in the way of merging difference and except in the way of, to new and old
Kinetic energy conversion effect is evaluated, and evaluation result is obtained.
Optionally, the new and old kinetic energy turnover of the second level includes: the GDP per capita for belonging to economic indicator, R&D intensity, three
Value added accounting, the level of urbanization, town and country income are produced than level-one new industry value added accounting；Belong to giving birth to per capita for power consumption index
Apply flexibly electricity, industrial electricity accounting, electric energy substitution level, electrified horizontal and power strength；Belong to the energy of energy efficiency indexes
Source strength, unit industrial added value energy consumption, non-fossil energy-consuming accounting, per capita energy consumption and crew, which work, to be produced
Rate.
Optionally, described according to different stage, it is utilized respectively Fuzzy B WM method and Index Weights is carried out to the index, really
The weight of fixed any index, comprising:
Fuzzy set in ambiguity in definition BWM method；
Obtain power index system to be assigned；
Described wait assign in power index system, optimal index and most bad index are determined；
According to the importance degree wait assign index and the optimal index and most bad index in power index system, really
Fixed fuzzy optimal judgement vector sum obscures most bad judgement vector；
Most bad judgement vector is obscured according to the fuzzy optimal judgement vector sum, calculates optimal fuzzy weight vector；
Using coincident indicator value, consistency desired result is carried out to the optimal fuzzy weight vector.
Optionally, the fuzzy set in the ambiguity in definition BWM method, comprising:
Define a Triangular Fuzzy NumberAnd the subordinating degree function of the Triangular Fuzzy Number is
To the Triangular Fuzzy Number de-fuzzy.
Optionally, the importance according to described wait assign index and the optimal index and most bad index in power index system
Degree, the method for determining the fuzzy most bad judgement vector of fuzzy optimal judgement vector sum, comprising:
It sets wait assign the comparison rule in power index system between each index；
Compare wait assign the importance degree in power index system between any index and optimal index, determines Quan Zhibiao to be assigned
Fuzzy optimal judgement vector in system
Compare wait assign the importance degree in power index system between any index and most bad index, determines Quan Zhibiao to be assigned
Fuzzy most bad judgement vector in system
Optionally, described to utilize coincident indicator value, consistency desired result, packet are carried out to the optimal fuzzy weight vector
It includes:
Most bad judgement vector is obscured according to fuzzy optimal judgement vector sum, determines the comparison knot of optimal index and most bad index
Fruit
According to the comparison result, coincident indicator value CI is determined using statistical method；
According to the optimal fuzzy weight vector and coincident indicator value, formula CR=k is utilized*/ CI calculates consistency ratio
Rate index, wherein CR is consistency ratio index, k*To solve obtained optimal Fuzzy B WM weight vectors and fuzzy optimal/most
Level of difference between bad judgement vector；
Judge the consistency ratio index whether less than 0.1；
If so, determining that the optimal fuzzy weight vector consistency desired result is qualified；
Otherwise, it is determined that the optimal fuzzy weight vector consistency desired result is unqualified；
Described wait assign in power index system, optimal index and most bad index are redefined.
Optionally, the weight according to different stage index, the grey correlation point in the way of merging difference and except in the way of
Analysis method evaluates new and old kinetic energy conversion effect, obtains evaluation result, comprising:
It determines ideal optimal sequence and sequence to be evaluated, includes that new and old kinetic energy conversion effect is commented in the ideal optimal sequence
The target value of each index in valence index system includes in new and old kinetic energy conversion effect assessment indicator system in the sequence to be evaluated
The actual value of index；
For large, minimal type and interval type index, it is utilized respectively formula WithThe ideal optimal sequence and sequence to be evaluated are carried out immeasurable
Guiding principle processing, obtains the ideal optimal sequence of standardization and the sequence to be evaluated of standardization；
In the way of merging difference and gray relative analysis method except in the way of, calculate the standardization ideal optimal sequence and
The degree of association between the sequence to be evaluated of standardization.
Optionally, the gray relative analysis method in the way of merging difference and except in the way of, calculates the reason of the standardization
Think the method for the degree of association between optimal sequence and the sequence to be evaluated of standardization, comprising:
It is utilized respectively formula Δ xij=| x0j-xij| and Δ x 'ij=xij/x0j, calculate standardization ideal optimal sequence and
The difference and quotient of each index in the sequence to be evaluated of standardization；
According to the difference of each index in the ideal optimal sequence of the standardization and the sequence to be evaluated of standardization, shape is constructed
Shape similitude grey relational grade γ1j(x0j,xij(the 1+ Δ x of)=1/ij)；
According to the quotient of each index in the ideal optimal sequence of the standardization and the sequence to be evaluated of standardization, construction away from
From proximity grey relational grade
According to the weight of different stage index, formula is utilizedIt will
The shape similarity grey relational grade and closely located property grey relational grade are integrated, and synthetical grey relation is calculated
Degree.
A kind of new and old kinetic energy conversion effect evaluation system, the system comprises:
Index system establishes module, and for establishing new and old kinetic energy conversion effect assessment indicator system, the new and old kinetic energy turns
The index changed into effect assessment indicator system includes the new and old kinetic energy turnover of level-one and the new and old kinetic energy turnover of second level, described
The new and old kinetic energy turnover of level-one includes: economic indicator, power consumption index and energy efficiency indexes, the new and old kinetic energy turnover of second level
For the index under the new and old kinetic energy turnover of the level-one；
Index Weights module, for being utilized respectively Fuzzy B WM method and carrying out index tax to the index according to different stage
Power, determines the weight of any index；
Overall merit module, the grey for the weight according to different stage index, in the way of merging difference and except in the way of
Correlation fractal dimension evaluates new and old kinetic energy conversion effect, obtains evaluation result.
Optionally, the Index Weights module includes:
Fuzzy set definition unit, for the fuzzy set in ambiguity in definition BWM method；
Wait assign power index system acquiring unit, for obtaining power index system to be assigned；
Optimal index and most bad index determination unit, for it is described wait assign power index system in, determine optimal index and
Most bad index；
Fuzzy Judgment vector determination unit, for according to the index and the optimal index wait assign in power index system
The importance degree of most bad index determines that fuzzy optimal judgement vector sum obscures most bad judgement vector；
Optimal fuzzy weight vector computing unit, for according to the fuzzy optimal judgement vector sum it is fuzzy most it is bad judge to
Amount, calculates optimal fuzzy weight vector；
Consistency desired result unit carries out consistency to the optimal fuzzy weight vector for utilizing coincident indicator value
Verification.
The technical solution that embodiments herein provides can include the following benefits:
The application provides a kind of new and old kinetic energy conversion effect evaluation method, which initially sets up new and old kinetic energy conversion
Effect assessment index system；Then it according to different stage, is utilized respectively Fuzzy B WM method and carries out Index Weights, determine any finger
Target weight；Finally according to the weight of different stage index, gray relative analysis method in the way of merging difference and except in the way of is right
New and old kinetic energy conversion effect is evaluated, and evaluation result is obtained.Wherein, in index system include economic indicator, power consumption index and
The new and old kinetic energy turnover of three level-ones of energy efficiency indexes and first class index two-level index below, the new and old kinetic energy are converted into
Assessment indicator system is imitated using power consumption index as core, is auxiliary with economic indicator and energy efficiency indexes, it can be more comprehensive and accurate
Evaluate effect of the power industry in the conversion of new and old kinetic energy in ground.The present embodiment carries out Index Weights, the party using Fuzzy B WM method
Method sets optimal and most bad reference sequences, can be effectively reduced switching judgement by combining fuzzy theory and BWM method
Inconsistency, additionally it is possible to avoid subjectivity of expert during judging that vector is constituted, be conducive to improve new and old kinetic energy and be converted into
The accuracy and reliability of effect.In integrated evaluating method, the present embodiment is using the poor mode of fusion and except the grey correlation point of mode
Analysis method can either consider new and old kinetic energy turnover data sequence from shape and apart from upper definition synthetical grey relation degree
Between geometric similarity degree, and it is contemplated that numerical value degree of closeness between new and old kinetic energy turnover data sequence, from
And further increase the accuracy and reliability of new and old kinetic energy conversion effect assessment.
The application also provides a kind of new and old kinetic energy conversion effect evaluation system, which mainly includes that index system establishes mould
Block, Index Weights module and overall merit module three parts.Module, which is established, by index system constructs the new and old kinetic energy conversion of level-one
Index and the new and old kinetic energy turnover of second level provide comprehensive index for the new and old kinetic energy conversion evaluation of subsequent progress, are conducive to mention
The accuracy of high new and old kinetic energy conversion effect assessment.The setting of Index Weights module, by mutually tying fuzzy theory with BWM method
It closes, can be effectively reduced the inconsistency of expert judgments, and avoid judging expert's subjectivity in vector construction process, thus greatly
The accuracy of new and old kinetic energy conversion effect assessment is improved greatly.The setting of overall merit module, by way of merging difference and except mode
Grey Incidence Analysis, between data sequence geometric similarity degree and data degree of closeness two in terms of define synthesis
Grey relational grade is conducive to the reliability and accuracy that further increase new and old kinetic energy conversion effect assessment.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
The application can be limited.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the application
Example, and together with specification it is used to explain the principle of the application.
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, for those of ordinary skill in the art
Speech, without creative efforts, is also possible to obtain other drawings based on these drawings.
Fig. 1 is a kind of flow diagram of new and old kinetic energy conversion effect evaluation method provided by the embodiment of the present application；
Fig. 2 is a kind of structural schematic diagram of new and old kinetic energy conversion effect evaluation system provided by the embodiment of the present application.
Specific embodiment
In order to make those skilled in the art better understand the technical solutions in the application, below in conjunction with the application reality
The attached drawing in example is applied, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that described implementation
Example is merely a part but not all of the embodiments of the present application.Based on the embodiment in the application, this field is common
The application protection all should belong in technical staff's every other embodiment obtained without making creative work
Range.
The application in order to better understand explains in detail presently filed embodiment with reference to the accompanying drawing.
Embodiment one
Referring to Fig. 1, Fig. 1 shows for a kind of process that new and old kinetic energy converts effect evaluation method provided by the embodiment of the present application
It is intended to.As shown in Figure 1, the new and old kinetic energy in the present embodiment converts effect evaluation method, mainly includes the following steps:
S1: establishing new and old kinetic energy conversion effect assessment indicator system, and new and old kinetic energy is converted in effect assessment indicator system
Index includes the new and old kinetic energy turnover of level-one and the new and old kinetic energy turnover of second level, and the new and old kinetic energy turnover of level-one includes:
Economic indicator, power consumption index and energy efficiency indexes, the new and old kinetic energy turnover of second level are the finger under the new and old kinetic energy turnover of level-one
Mark.
In the present embodiment the new and old kinetic energy turnover of second level include: the new and old kinetic energy turnover of second level under economic indicator,
The new and old kinetic energy turnover of second level under power consumption index and the new and old kinetic energy turnover of second level under energy efficiency indexes.Wherein, economical
Index includes: GDP per capita, R&D intensity, tertiary industry value added accounting, the level of urbanization, town and country income than the increase of level-one new industry
It is worth accounting；Power consumption index include: per capita domestic load, industrial electricity accounting, electric energy substitution level, it is electrified horizontal and
Power strength；Energy efficiency indexes include: Energy Intensity, unit industrial added value energy consumption, non-fossil energy-consuming accounting, per capita energy
Consumption figure and overall labour productivity.Specifically, new and old kinetic energy conversion effect assessment indicator system can join in the present embodiment
See such as the following table 1.
The new and old kinetic energy of table 1 converts effect assessment indicator system
By the above table 1 it is found that in the new and old kinetic energy conversion effect assessment indicator system, the new and old kinetic energy conversion of different second levels
Index has different Criterion Attributes, and power consumption index is core index, and the Criterion Attribute of two-level index is mostly regional computer finger
Mark, economic indicator and energy efficiency indexes are auxiliary characteristics.
S2: it according to different stage, is utilized respectively Fuzzy B WM method and Index Weights is carried out to index, determine any index
Weight.
Specifically, step S2 is comprised the following processes:
S21: the fuzzy set in ambiguity in definition BWM method.
In the present embodiment when determining weight using Fuzzy B WM method, need to define a Fuzzy B WM method use first
Fuzzy set type, when subsequent progress index importance judgement, the fuzzy number that is used uniformly under the fuzzy set form.The present embodiment
Middle to use Triangular Fuzzy Number, specifically, step S21 is comprised the following processes:
S211: a Triangular Fuzzy Number is definedIts subordinating degree function is
S212: to Triangular Fuzzy Number de-fuzzy.
Utilize formulaTo Triangular Fuzzy Number de-fuzzy, by Triangular Fuzzy Number deblurring
Change, be transformed into real number, in order to which the subsequent weights that Fuzzy B WM method is calculated are applied to overall merit.
The rudimentary algorithm of the present embodiment intermediate cam fuzzy number further include:
After fuzzy set in ambiguity in definition BWM method, executes step S22: obtaining power index system to be assigned.
Assuming that shared n Quan Zhibiao to be assigned, are denoted as: C=(c1,c2,…,cn).It is new and old to level-one dynamic first in the present embodiment
Can turnover be carry out tax power, wait assign power index there are three: economic indicator, power consumption index and energy efficiency indexes.
S23: wait assign in power index system, optimal index and most bad index are determined.
In n wait assign in power index, it is determined as optimal index for index weights are maximum, is denoted as CB, most by index weights
Small is determined as most bad index, is denoted as CW.In the present embodiment, by taking the new and old kinetic energy turnover of three level-ones as an example, optimal index
For power consumption index, most bad index is economic indicator.
S24: according to the importance degree wait assign index and optimal index and most bad index in power index system, mould is determined
It pastes optimal judgement vector sum and obscures most bad judgement vector.
Specifically, step S24 is comprised the following processes again:
S241: it sets wait assign the comparison rule in power index system between each index.
Under the present embodiment intermediate cam fuzzy number, the comparison rule between the new and old kinetic energy turnover of level-one is as shown in table 2 below.
| Importance judgement | Fuzzy membership |
| No less important | (1,1,1) |
| It is slightly important | (2/3,1,3/2) |
| It is general important | (3/2,2,5/2) |
| It is extremely important | (5/2,3,7/2) |
| It is absolutely essential | (7/2,4,9/2) |
Indexes Comparison rule under 2 Fuzzy B WM of table
S242: compare wait assign the importance degree in power index system between any index and optimal index, determine wait assign
Weigh the fuzzy optimal judgement vector in index system
The importance degree being respectively compared between the new and old kinetic energy turnover of three level-ones and optimal index, obtains level-one and refers to
Mark fuzzy optimal judgement vectorIn formula,It is optimal index and index CjIt compares
Fuzzy importance.Since optimal index compares no less important with its own, have in fuzzy optimal judgement vectorThe fuzzy optimal judgement vector of first class index in the present embodiment are as follows:
S243: compare wait assign the importance degree in power index system between any index and most bad index, determine wait assign
Weigh the fuzzy most bad judgement vector in index system
Similarly, it in step S243, is respectively compared important between the new and old kinetic energy turnover of three level-ones and most bad index
Property degree, obtain first class index obscure most bad judgement vectorIn formula,Refer to
Mark CjThe fuzzy importance that most bad index is compared.Since most bad index compares no less important with its own, obscure most bad
Judge have in vectorFirst class index obscures most bad judgement vector in the present embodiment are as follows:
The step S241-S243 of the present embodiment obscures most bad judgement vector by the fuzzy optimal judgement vector sum of determination, makes
The judging result that must transfer is more in line with reality, advantageously reduces the subjectivity of expert, comments to improve new and old kinetic energy conversion effect
The accuracy of valence.
S25: most bad judgement vector is obscured according to fuzzy optimal judgement vector sum, calculates optimal fuzzy weight vector.
The optimal weights of Fuzzy B WM method meet in the present embodiment: the practical fuzzy weighted values of each index and optimal index
The relationship of fuzzy weighted values should be close to the optimal judgement vector constructed, the practical fuzzy weighted values of each index and most bad finger as far as possible
The relationship of target fuzzy weighted values should be close to the most bad judgement vector constructed as far as possible.I.e. for any index Cj,WithIt should level off to 0 as far as possible.Based on this principle, can be obtained by solving following optimization problems
To the optimal weights vector of Fuzzy B WM, that is, optimal fuzzy weight vector:
In formula,In the present embodiment, according to one
The fuzzy optimal judgement vector sum of the new and old kinetic energy turnover of grade obscures most bad judgement vector, solves three new and old kinetic energy of level-one and turns
Change the fuzzy weight vector of index, i.e. j=1,2,3.Since the objective function of formula (1) includes simultaneously that maximization and minimum are asked
Topic, can will convert following nonlinear optimal problems for formula (1), in order to carry out model solution:
In formula,Due to lξ≤mξ≤uξ, enableThen formula (2) can be write
At:
Solution formula (3), can be obtained optimal fuzzy weight vectorIn the present embodiment, solve
To the optimal fuzzy weight vector of the new and old kinetic energy turnover of three level-ones are as follows:
The present embodiment calculates optimal fuzzy weight vector, realizes the optimization of fuzzy weight vector by step S25, thus
The subjectivity of expert judgments is reduced by Mathematical process, so improve new and old kinetic energy conversion effect assessment accuracy and can
By property.
S26: utilizing coincident indicator value, carries out consistency desired result to optimal fuzzy weight vector.
The present embodiment can be avoided the inconsistent of expert judgments, to reduce the subjectivity of expert judgments by step S26
Property, be conducive to the reliability for improving new and old kinetic energy conversion.
Specifically, step S26 is comprised the following processes again:
S261: most bad judgement vector is obscured according to fuzzy optimal judgement vector sum, determines optimal index and most bad index
Comparison result
It is the important sexual intercourse between optimal index and most bad index, i.e., fuzzy optimal judgement vector sum is fuzzy most
The maximum Triangular Fuzzy Number of index otherness in bad judgement vector.
S262: according to comparison result, coincident indicator value CI is determined using statistical method.
Fuzzy B WM coincident indicator value is as shown in table 3 below in the present embodiment:
3 Fuzzy B WM coincident indicator value list of table
S263: according to optimal fuzzy weight vector and coincident indicator value, formula CR=k is utilized*/ CI calculates consistency ratio
Rate index.
Wherein, CR is consistency ratio index, k*For solve obtained optimal Fuzzy B WM weight vectors and fuzzy optimal/
Level of difference between most bad judgement vector, k*It can solve to obtain together when solving optimal Fuzzy B WM weight vectors, CI mono-
Cause property index value.
S264: judge consistency ratio index whether less than 0.1.
If consistency ratio index less than 0.1, executes step S265: determining optimal fuzzy weight vector consistency desired result
It is qualified.
WithFor, as shown in Table 3,Corresponding CI value is 8.04, and solution formula (3) can obtainTherefore, k*=0.4495.Utilize formula CR=k*/ CI can obtain CR=0.4495/8.04=
0.0559 < 0.1, determine that optimal fuzzy weight vector consistency desired result is qualified.
Determine that optimal fuzzy weight vector consistency desired result is qualified and then utilizes formulaBy three one
The Triangular Fuzzy Number of the new and old kinetic energy turnover of grade is converted to real number.That is: when consistency desired result qualification, show that the present embodiment obtains
To index Fuzzy weight vectors be it is believable, for by these index Fuzzy weights be applied to new and old kinetic energy effect conversion evaluation
In, need to be converted to fuzzy weighted values real number weights, the de-fuzzy of the new and old kinetic energy turnover of three level-ones in the present embodiment
Weight is respectively as follows:
If consistency ratio index is more than or equal to 0.1, executes step S266: determining optimal fuzzy weight vector consistency
It verifies unqualified.
When determining that optimal fuzzy weight vector consistency desired result is unqualified, de-fuzzy at this time, that is, nonsensical is needed
Return step S23 is wanted, optimal index and most bad index are redefined.
The step side that index weights are solved with Fuzzy B WM method is given by taking the new and old kinetic energy turnover of level-one as an example above
Method similarly can respectively convert the new and old kinetic energy of second level under the new and old kinetic energy turnover of three level-ones with same procedure
Index carries out Index Weights.
In the present embodiment, there are 6 wait assign power index in economic indicator, optimal index is new industry value added accounting,
Most bad index is the level of urbanization；There are 5 wait assign power index in power consumption index, optimal index is electrified horizontal, most bad finger
It is designated as power strength；There are 5 wait assign power index in energy efficiency indexes, optimal index is overall labour productivity, and most bad index is
Per capita energy consumption.
The process of Index Weights is carried out to the new and old kinetic energy turnover of second level are as follows: be respectively compared the new and old kinetic energy of each level-one and turn
The importance degree for changing second level new and old the kinetic energy turnover and optimal index in index obtains the new and old kinetic energy conversion of each level-one
The fuzzy optimal judgement vector of the new and old kinetic energy turnover of second level under index；It is respectively compared the new and old kinetic energy turnover of each level-one
In second level new and old kinetic energy turnover and most bad index importance degree, obtain under the new and old kinetic energy turnover of each level-one
The fuzzy most bad judgement vector of the new and old kinetic energy turnover of second level.It was solved then referring to the new and old kinetic energy turnover weight of level-one
The new and old kinetic energy turnover of second level under the new and old kinetic energy turnover of each level-one is calculated according to formula (1)~(3) in journey
Fuzzy B WM weight vectors, according to formula CR=k*/ CI judges the consistency of weights, finally by Fuzzy B WM weight vectors
It is converted into real number, in order to which Fuzzy B WM weights are applied in overall merit.
The index weights calculating knot of all level-one new and old kinetic energy turnovers and the new and old kinetic energy conversion of second level in the present embodiment
Fruit is as shown in table 4:
Index weights calculated result of the table 4 based on Fuzzy B WM
With continued reference to Fig. 1 it is found that carrying out Index Weights to the index using Fuzzy B WM method, any index is determined
After weight, step S3 is executed: the grey correlation point according to the weight of different stage index, in the way of merging difference and except in the way of
Analysis method evaluates new and old kinetic energy conversion effect, obtains evaluation result.
Specifically, step S3 is comprised the following processes:
S31: determining ideal optimal sequence and sequence to be evaluated, includes that new and old kinetic energy conversion effect is commented in ideal optimal sequence
The target value of each index in valence index system includes index in new and old kinetic energy conversion effect assessment indicator system in sequence to be evaluated
Actual value.
Defining ideal optimal sequence is XO, defining sequence to be evaluated is Xi=(xi1,xi2,…,xin), to illustrate to utilize fusion
Poor mode and except the gray relative analysis method of mode is to the process evaluated of new and old kinetic energy conversion effect, the present embodiment is with a certain
For new and old kinetic energy conversion effect assessment case, it is assumed that new and old kinetic energy conversion effect index value is as shown in table 5 in the case:
| Index serial number | Target value | Certain year actual value |
| S11 | 82212 | 65040 |
| S12 | 0.027 | 0.0223 |
| S13 | 0.55 | 0.4482 |
| S14 | 0.62 | 0.5701 |
| S15 | 2.38 | 2.4396 |
| S16 | 0.16 | 0.0798 |
| S21 | 850 | 512.6 |
| S22 | [0.7,0.74] | 0.7950 |
| S23 | [1.8,2.2] | 1.62 |
| S24 | [0.6,0.7] | 0.5448 |
| S25 | [0.021,0.048] | 0.0812 |
| S31 | 0.0493 | 0.0594 |
| S32 | 0.10 | 0.1358 |
| S33 | 18 | 6.33 |
| S34 | 4034 | 3.8534 |
| S35 | 14 | 9.4256 |
New and old kinetic energy converts effect index value in certain case of table 5
S32: it is directed to large, minimal type and interval type index, is utilized respectively formula WithIdeal optimal sequence and sequence to be evaluated are carried out at dimensionless
Reason, obtains the ideal optimal sequence of standardization and the sequence to be evaluated of standardization.
After getting ideal optimal sequence and sequence to be evaluated, data normalization processing, this implementation are carried out to it respectively
It is substantially carried out dimensionless processing in example, is handled by data normalization, the sequence of nondimensionalization and unification can be obtained, and advise
Data after generalized are in [0,1] section.
Since ideal optimal sequence is new and old kinetic energy conversion effect target value, it can thus be assumed that the ideal after standardization is most
Dominating sequence gets the maximum value of the index in each index, i.e., the sequence for ideal optimal sequence, after setting standardization
Are as follows: X '0=(1,1 ..., 1)T,
For sequence X to be evaluatedi=[xij]1×n, according to index property set standardization sequence X 'i。
For large index, sequence to be evaluated of standardizing are as follows:
For minimal type index, sequence to be evaluated of standardizing are as follows:
For interval type index, sequence to be evaluated of standardizing are as follows:
In this hair embodiment, the standardization sequence of sequence to be evaluated are as follows:
X′i=(0.7911,0.8277,0.8149,0.9195,0.9756,0.4988,0.6031,0.9308,0.9018,
0.90 80,0.5911,0.8300,0.7363,0.3517,0.9552,0.6733)。
S33: in the way of merging difference and gray relative analysis method except in the way of, calculate standardization ideal optimal sequence and
The degree of association between the sequence to be evaluated of standardization.
Specifically, step S33 is comprised the following processes again:
S331: it is utilized respectively formula Δ xij=| x0j-xij| and Δ x 'ij=xij/x0j, calculate the optimal sequence of ideal of standardization
The difference and quotient of each index in column and the sequence to be evaluated of standardization.
S332: according to the difference of each index in the ideal optimal sequence of standardization and the sequence to be evaluated of standardization, construction
Shape similarity grey relational grade γ1j(x0j,xij(the 1+ Δ x of)=1/ij)。
According to the principle that the difference of each index is closer to 0 in two sequences, then two sequences are closer, and structure form is similar
Property grey relational grade, can be from the angle of the geometric similarity degree between data sequence, to judge between actual value and target value
Relevance.
S333: according to the quotient of each index in the ideal optimal sequence of standardization and the sequence to be evaluated of standardization, construction
Closely located property grey relational grade
According to the principle that the quotient of each index is closer to 1 in two sequences, then two sequences are closer, construct closely located
Property grey relational grade, can be from the angle of the numerical value degree of closeness between data sequence, to judge between actual value and target value
Relevance.
S334: according to the weight of different stage index, formula is utilizedBy shape similarity grey relational grade and closely located property grey correlation
Degree is integrated, and synthetical grey relation degree is calculated.
The present embodiment obtains final summation grey correlation by comprehensively considering shape and apart from upper grey relational grade
Degree, the grey relational grade is more accurate, so as to effectively improve the reliability of new and old kinetic energy conversion effect assessment.
It is available according to new and old kinetic energy converts effect index value in certain case in table 5 using the method in the present embodiment
New and old kinetic energy converts effect evaluation result in the case, as shown in table 6.
New and old kinetic energy converts effect evaluation result in certain case of table 6
Embodiment two
On the basis of embodiment shown in Fig. 1 referring to fig. 2, Fig. 2 is that one kind provided by the embodiment of the present application is new and old dynamic
The structural schematic diagram of effect evaluation system can be converted.As shown in Figure 2, the new and old kinetic energy in the present embodiment converts effect assessment system
System, specifically includes that index system establishes module, Index Weights module and overall merit module.
Wherein, index system establishes module, and for establishing new and old kinetic energy conversion effect assessment indicator system, new and old kinetic energy turns
The index changed into effect assessment indicator system includes the new and old kinetic energy turnover of level-one and the new and old kinetic energy turnover of second level, level-one
New and old kinetic energy turnover includes: economic indicator, power consumption index and energy efficiency indexes, and the new and old kinetic energy turnover of second level is that level-one is new
Index under old kinetic energy turnover.Index Weights module is used to be utilized respectively Fuzzy B WM method to finger according to different stage
Mark carries out Index Weights, determines the weight of any index.Overall merit module, for the weight according to different stage index, benefit
With merging poor mode and removing the gray relative analysis method of mode, new and old kinetic energy conversion effect is evaluated, evaluation result is obtained.
Further, in this embodiment Index Weights module include: fuzzy set definition unit, wait assign power index system obtain
Unit, optimal index and most bad index determination unit, fuzzy Judgment vector determination unit, optimal fuzzy weight vector is taken to calculate list
Member and consistency desired result unit.Wherein, fuzzy set definition unit is for the fuzzy set in ambiguity in definition BWM method；Power to be assigned refers to
Mark system acquiring unit is for obtaining power index system to be assigned；Optimal index and most bad index determination unit, for wait assign power
In index system, optimal index and most bad index are determined；Fuzzy Judgment vector determination unit, for according to power index system to be assigned
In index and optimal index and most bad index importance degree, determine fuzzy optimal judgement vector sum obscure most it is bad judge to
Amount；Optimal fuzzy weight vector computing unit calculates most for obscuring most bad judgement vector according to fuzzy optimal judgement vector sum
Excellent fuzzy weight vector；Consistency desired result unit carries out optimal fuzzy weight vector consistent for utilizing coincident indicator value
Property verification.
Fuzzy Judgment vector determination unit includes: comparison rule setting subelement, the determining son of fuzzy optimal judgement vector again
Unit and fuzzy most bad judgement vector determine subelement.Wherein, comparison rule sets subelement, for setting wait assign power index body
Comparison rule in system between each index；Fuzzy optimal judgement vector determines subelement, appoints for comparing wait assign in power index system
Importance degree between one index and optimal index is determined wait assign the fuzzy optimal judgement vector in power index systemFuzzy most bad judgement vector determines subelement, for comparing wait assign in power index system
Importance degree between any index and most bad index is determined wait assign the fuzzy most bad judgement vector in power index system
Consistency desired result unit includes: that comparison result determines that subelement, coincident indicator value determine subelement, consistency again
Ratio indicator computation subunit and judgment sub-unit.Wherein, comparison result determines subelement, for according to it is fuzzy optimal judge to
Amount and fuzzy most bad judgement vector, determine the comparison result of optimal index and most bad indexCoincident indicator value determines son
Unit, for determining coincident indicator value using statistical method according to comparison result；Consistency ratio index computation subunit,
For utilizing formula CR=k according to optimal fuzzy weight vector and coincident indicator value*/ CI calculates consistency ratio index,
In, CR is consistency ratio index, k*For solve obtained optimal Fuzzy B WM weight vectors and fuzzy optimal/most it is bad judge to
Level of difference between amount obtains together when solving optimal Fuzzy B WM weight vectors, and CI is coincident indicator value；Judgement is single
Member, for judging that consistency ratio index whether less than 0.1, when consistency ratio index is less than 0.1, determines optimal fuzzy weight
Weight vector consistency verification is qualified, otherwise, it is determined that optimal fuzzy weight vector consistency desired result is unqualified.And when the optimal mould of judgement
When paste weight vectors consistency desired result is unqualified, start optimal index and most bad index determination unit.
The working principle and working method of new and old kinetic energy conversion effect evaluation system, reality shown in Fig. 1 in the present embodiment
Apply in example and elaborated, between two embodiments can mutual reference, details are not described herein.
The above is only the specific embodiment of the application, is made skilled artisans appreciate that or realizing this Shen
Please.Various modifications to these embodiments will be apparent to one skilled in the art, as defined herein
General Principle can be realized in other embodiments without departing from the spirit or scope of the application.Therefore, the application
It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one
The widest scope of cause.
Claims (10)
1. a kind of new and old kinetic energy converts effect evaluation method, which is characterized in that the described method includes:
Establish new and old kinetic energy conversion effect assessment indicator system, the index in the new and old kinetic energy conversion effect assessment indicator system
Including the new and old kinetic energy turnover of level-one and the new and old kinetic energy turnover of second level, the new and old kinetic energy turnover of level-one includes:
Economic indicator, power consumption index and energy efficiency indexes, the new and old kinetic energy turnover of second level are that the new and old kinetic energy conversion of the level-one refers to
Index under mark；
According to different stage, it is utilized respectively Fuzzy B WM method and Index Weights is carried out to the index, determine the power of any index
Weight；
According to the weight of different stage index, gray relative analysis method in the way of merging difference and except in the way of, to new and old kinetic energy
Conversion effect is evaluated, and evaluation result is obtained.
2. a kind of new and old kinetic energy according to claim 1 converts effect evaluation method, which is characterized in that the second level is new and old
Kinetic energy turnover includes: the GDP per capita for belonging to economic indicator, R&D intensity, tertiary industry value added accounting, the level of urbanization, town and country
Income is than level-one new industry value added accounting；Belong to domestic load per capita, the industrial electricity accounting, electric energy of power consumption index
Substitution level, electrified horizontal and power strength；Belong to the Energy Intensity of energy efficiency indexes, unit industrial added value energy consumption, non-
Fossil energy consumes accounting, per capita energy consumption and overall labour productivity.
3. a kind of new and old kinetic energy according to claim 1 converts effect evaluation method, which is characterized in that described according to difference
Rank is utilized respectively Fuzzy B WM method and carries out Index Weights to the index, determines the weight of any index, comprising:
Fuzzy set in ambiguity in definition BWM method；
Obtain power index system to be assigned；
Described wait assign in power index system, optimal index and most bad index are determined；
According to the importance degree wait assign index and the optimal index and most bad index in power index system, mould is determined
It pastes optimal judgement vector sum and obscures most bad judgement vector；
Most bad judgement vector is obscured according to the fuzzy optimal judgement vector sum, calculates optimal fuzzy weight vector；
Using coincident indicator value, consistency desired result is carried out to the optimal fuzzy weight vector.
4. a kind of new and old kinetic energy according to claim 3 converts effect evaluation method, which is characterized in that the ambiguity in definition
Fuzzy set in BWM method, comprising:
Define a Triangular Fuzzy NumberAnd the subordinating degree function of the Triangular Fuzzy Number is
To the Triangular Fuzzy Number de-fuzzy.
5. a kind of new and old kinetic energy according to claim 3 converts effect evaluation method, which is characterized in that according to described wait assign
The importance degree for weighing the index and the optimal index and most bad index in index system, determines fuzzy optimal judgement vector sum
The method of fuzzy most bad judgement vector, comprising:
It sets wait assign the comparison rule in power index system between each index；
Compare wait assign the importance degree in power index system between any index and optimal index, determines power index system to be assigned
In fuzzy optimal judgement vector
Compare wait assign the importance degree in power index system between any index and most bad index, determines power index system to be assigned
In fuzzy most bad judgement vector
6. a kind of new and old kinetic energy according to claim 3 converts effect evaluation method, which is characterized in that described using consistent
Property index value, consistency desired result is carried out to the optimal fuzzy weight vector, comprising:
Most bad judgement vector is obscured according to fuzzy optimal judgement vector sum, determines the comparison result of optimal index and most bad index
According to the comparison result, coincident indicator value CI is determined using statistical method；
According to the optimal fuzzy weight vector and coincident indicator value, formula CR=k is utilized*/ CI calculates consistency ratio and refers to
Mark, wherein CR is consistency ratio index, k*Sentence to solve obtained optimal Fuzzy B WM weight vectors with fuzzy optimal/most bad
Level of difference between disconnected vector；
Judge the consistency ratio index whether less than 0.1；
If so, determining that the optimal fuzzy weight vector consistency desired result is qualified；
Otherwise, it is determined that the optimal fuzzy weight vector consistency desired result is unqualified；
Described wait assign in power index system, optimal index and most bad index are redefined.
7. a kind of new and old kinetic energy according to claim 1 converts effect evaluation method, which is characterized in that described according to difference
The weight of level index, the gray relative analysis method in the way of merging difference and except in the way of carry out new and old kinetic energy conversion effect
Evaluation obtains evaluation result, comprising:
It determines ideal optimal sequence and sequence to be evaluated, includes that new and old kinetic energy conversion effect assessment refers in the ideal optimal sequence
The target value of each index in mark system includes index in new and old kinetic energy conversion effect assessment indicator system in the sequence to be evaluated
Actual value；
For large, minimal type and interval type index, it is utilized respectively formula WithThe ideal optimal sequence and sequence to be evaluated are carried out immeasurable
Guiding principle processing, obtains the ideal optimal sequence of standardization and the sequence to be evaluated of standardization；
Gray relative analysis method in the way of merging difference and except in the way of, calculates the ideal optimal sequence and specification of the standardization
The degree of association between sequence to be evaluated changed.
8. a kind of new and old kinetic energy according to claim 7 converts effect evaluation method, which is characterized in that described to utilize fusion
Poor mode and gray relative analysis method except mode, calculate the ideal optimal sequence of the standardization and the sequence to be evaluated of standardization
The method of the degree of association between column, comprising:
It is utilized respectively formula Δ xij=| x0j-xij| and Δ x 'ij=xij/x0j, calculate the ideal optimal sequence and specification of standardization
The difference and quotient of each index in the sequence to be evaluated changed；
According to the difference of each index in the ideal optimal sequence of the standardization and the sequence to be evaluated of standardization, structure form phase
Like property grey relational grade γ1j(x0j,xij(the 1+ Δ x of)=1/ij)；
According to the quotient of each index in the ideal optimal sequence of the standardization and the sequence to be evaluated of standardization, construct apart from phase
Nearly property grey relational grade
According to the weight of different stage index, formula is utilizedIt will be described
Shape similarity grey relational grade and closely located property grey relational grade are integrated, and synthetical grey relation degree is calculated.
9. a kind of new and old kinetic energy converts effect evaluation system, which is characterized in that the system comprises:
Index system establishes module, and for establishing new and old kinetic energy conversion effect assessment indicator system, the new and old kinetic energy is converted into
The index imitated in assessment indicator system includes the new and old kinetic energy turnover of level-one and the new and old kinetic energy turnover of second level, the level-one
New and old kinetic energy turnover includes: economic indicator, power consumption index and energy efficiency indexes, and the new and old kinetic energy turnover of second level is institute
State the index under the new and old kinetic energy turnover of level-one；
Index Weights module, for being utilized respectively Fuzzy B WM method and carrying out Index Weights to the index according to different stage,
Determine the weight of any index；
Overall merit module, the grey correlation for the weight according to different stage index, in the way of merging difference and except in the way of
Analytic approach evaluates new and old kinetic energy conversion effect, obtains evaluation result.
10. a kind of new and old kinetic energy according to claim 9 converts effect evaluation system, which is characterized in that the index is assigned
Weighing module includes:
Fuzzy set definition unit, for the fuzzy set in ambiguity in definition BWM method；
Wait assign power index system acquiring unit, for obtaining power index system to be assigned；
Optimal index and most bad index determination unit, for, wait assign in power index system, determining optimal index and most bad described
Index；
Fuzzy Judgment vector determination unit, for according to described wait assign index in power index system and the optimal index and most
The importance degree of bad index determines that fuzzy optimal judgement vector sum obscures most bad judgement vector；
Optimal fuzzy weight vector computing unit, for obscuring most bad judgement vector according to the fuzzy optimal judgement vector sum,
Calculate optimal fuzzy weight vector；
Consistency desired result unit carries out consistency desired result to the optimal fuzzy weight vector for utilizing coincident indicator value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910365737.6A CN110264030A (en) | 2019-04-29 | 2019-04-29 | A kind of new and old kinetic energy conversion effect evaluation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910365737.6A CN110264030A (en) | 2019-04-29 | 2019-04-29 | A kind of new and old kinetic energy conversion effect evaluation method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110264030A true CN110264030A (en) | 2019-09-20 |
Family
ID=67914093
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910365737.6A Pending CN110264030A (en) | 2019-04-29 | 2019-04-29 | A kind of new and old kinetic energy conversion effect evaluation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110264030A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111191328A (en) * | 2019-12-19 | 2020-05-22 | 北京交通大学 | Comprehensive importance evaluation method for bogie component based on multiple complex networks |
| CN113128912A (en) * | 2021-05-14 | 2021-07-16 | 华北电力大学 | Method for determining conversion level of new kinetic energy and old kinetic energy of industry based on power consumption data |
| CN113554340A (en) * | 2021-08-05 | 2021-10-26 | 国网山东省电力公司经济技术研究院 | Big data-based electricity selling company credit assessment method and device |
| CN113554339A (en) * | 2021-08-05 | 2021-10-26 | 国网山东省电力公司经济技术研究院 | New energy power generator credit evaluation method and device, equipment and storage medium |
| CN115907565A (en) * | 2023-02-14 | 2023-04-04 | 清华四川能源互联网研究院 | Diversion tunnel structure safety evaluation method and device, electronic equipment and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9355460B1 (en) * | 2015-03-20 | 2016-05-31 | Top Vicotry Investments Ltd. | Motion detection method based on grey relational analysis |
| CN106127388A (en) * | 2016-06-24 | 2016-11-16 | 南瑞（武汉）电气设备与工程能效测评中心 | The energy efficiency evaluating method of high energy-consuming enterprises |
-
2019
- 2019-04-29 CN CN201910365737.6A patent/CN110264030A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9355460B1 (en) * | 2015-03-20 | 2016-05-31 | Top Vicotry Investments Ltd. | Motion detection method based on grey relational analysis |
| CN106127388A (en) * | 2016-06-24 | 2016-11-16 | 南瑞（武汉）电气设备与工程能效测评中心 | The energy efficiency evaluating method of high energy-consuming enterprises |
Non-Patent Citations (3)
| Title |
|---|
| 吴云等: "基于改进灰色关联分析与蝙蝠优化神经网络的短期负荷预测", 《电力系统自动化》 * |
| 杨雍琦等: "支撑新旧动能转换的综合能源系统效率评价", 《济南大学学报(自然科学版)》 * |
| 贾凡: ""不确定信息环境下多准则群决策方法研究"", 《中国博士学位论文全文数据库》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111191328A (en) * | 2019-12-19 | 2020-05-22 | 北京交通大学 | Comprehensive importance evaluation method for bogie component based on multiple complex networks |
| CN113128912A (en) * | 2021-05-14 | 2021-07-16 | 华北电力大学 | Method for determining conversion level of new kinetic energy and old kinetic energy of industry based on power consumption data |
| CN113128912B (en) * | 2021-05-14 | 2024-02-27 | 华北电力大学 | Method for determining industry new and old kinetic energy conversion level based on electricity consumption data |
| CN113554340A (en) * | 2021-08-05 | 2021-10-26 | 国网山东省电力公司经济技术研究院 | Big data-based electricity selling company credit assessment method and device |
| CN113554339A (en) * | 2021-08-05 | 2021-10-26 | 国网山东省电力公司经济技术研究院 | New energy power generator credit evaluation method and device, equipment and storage medium |
| CN115907565A (en) * | 2023-02-14 | 2023-04-04 | 清华四川能源互联网研究院 | Diversion tunnel structure safety evaluation method and device, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110264030A (en) | A kind of new and old kinetic energy conversion effect evaluation method and system | |
| Wei et al. | Induced hesitant interval-valued fuzzy Einstein aggregation operators and their application to multiple attribute decision making | |
| Zeng et al. | A projection method for multiple attribute group decision making with intuitionistic fuzzy information | |
| Zhao et al. | Extended VIKOR method based on cross-entropy for interval-valued intuitionistic fuzzy multiple criteria group decision making | |
| CN108632764B (en) | Multi-sensor selective measurement data fusion estimation method | |
| CN110458385B (en) | Large-scale enterprise supply and demand party matching method based on three decisions | |
| CN106228184A (en) | A kind of based on the blast furnace fault detection system and the method that optimize extreme learning machine | |
| CN109165807A (en) | A kind of energy quality comprehensive assessment method based on probabilistic neural network | |
| CN113343427B (en) | Structural topology configuration prediction method based on convolutional neural network | |
| CN110135643A (en) | Consider the Short-term Load Forecast method of steel forward price and Spot Price factor | |
| Jia et al. | Interval‐Valued Intuitionistic Fuzzy Multiple Attribute Group Decision Making with Uncertain Weights | |
| CN109615246B (en) | Method for determining economic operation state of active power distribution network | |
| CN111523768A (en) | Entropy weight-TOPSIS-based generalized demand side resource quality evaluation method | |
| Liu et al. | An improved Elman network for stock price prediction service | |
| Xiang et al. | High-end equipment: An improved two-sided based S&M matching and a novel Pareto refining method considering consistency | |
| CN112966914B (en) | Intelligent quality control method for assembled transformer substation based on GIM-5D | |
| Kan et al. | Stock price prediction based on artificial neural network | |
| Shahriari | Soft computing based on a modified MCDM approach under intuitionistic fuzzy sets | |
| Cong et al. | New smart city clusters’ construction level evaluation under economic circles: the case of Shandong, China | |
| Jia et al. | The cultivation quality evaluation of international talents based on deep learning | |
| LU503411B1 (en) | Method and system for evaluating new and old kinetic energy conversion effect | |
| Guo et al. | Short-term stock forecasting based on phase space reconstruction and cluster analysis | |
| Liu | The analysis of differential high-quality development of economy by deep neural network and internet of things | |
| CN109784723A (en) | Power transmission and transformation Project Risk Evaluation and terminal device | |
| Gao et al. | A Similarity Measurement Method Based on Graph Kernel for Disconnected Graphs. |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190920 |
|
| RJ01 | Rejection of invention patent application after publication |