CN109146259A - A kind of independent sale of electricity development of company Assessment Method on Potential based on grey Cluster Evaluation - Google Patents
A kind of independent sale of electricity development of company Assessment Method on Potential based on grey Cluster Evaluation Download PDFInfo
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Abstract
The invention discloses a kind of independent sale of electricity development of company Assessment Method on Potential based on grey Cluster Evaluation for belonging to Management of Electrical Enterprise technical field.It include: that step 1 determines evaluation object；Step 2 determines evaluation index according to the data of acquisition；Step 3 establishes assessment indicator system；Step 4 index cluster, using Grey Correlation Cluster, analyzes the index in index system, and delete the index in index system；Step 5 evaluates the development potentiality of independent sale of electricity company with the index system after deleting based on the sale of electricity development of company Potential Evaluation model that endpoint triangle albefaction is weighed.The present invention is able to carry out the comparison of multiple sale of electricity companies, finds the potentiality of different sale of electricity companies, is advised according to result；The difficulty of data collection and processing is reduced, is improved efficiency to carry out the evaluation of a large amount of independent sale of electricity companies；The comprehensively difference and strengths and weaknesses of more each sale of electricity company lays the foundation to excavate the development potentiality of independent sale of electricity company.
Description
Technical field
The invention belongs to Management of Electrical Enterprise fields, and in particular to a kind of independent sale of electricity company based on grey Cluster Evaluation
Development potentiality evaluation method.
Background technique
Open the power market reform of a new round in March, 2015, the market-oriented reform of sale of electricity link is this electric power row
The innovative point of industry reform；This time reform the competitive link electricity price orderly decontroled other than transmission & distribution, orderly opens and match to social capital
Sale of electricity business orderly decontrols the hair electricity plan other than public welfare and modulability.
Occurs three classes sale of electricity main body after sale of electricity side is decontroled completely, in market, including the separation establishment from grid company
Sale of electricity company and other enterprises that sale of electricity company, electricity power enterprise set up and the sale of electricity company that non-governmental capital is set up, referred to as independently sell
Electric company.Compared to Qian Lianglei sale of electricity company, independent sale of electricity company both without power network resources or without generation assets, was in a disadvantageous position
Status, but the advantage not having with preceding two classes sale of electricity main body again, as decision is flexible, capital operation ability is strong, the marketing
The strong and huge customer group etc. of ability.According to Guangdong Province's sale of electricity data, Guangdong electric power saving exchange hand in 2017 is 113,800,000,000 thousand
Watt-hour, the sale of electricity company for participating in marketing have 135, and wherein power plant's background sale of electricity company accounts for entire power market transaction
Half share, independent sale of electricity company transaction electricity account for 43%.It can be seen that independent sale of electricity company is compared with other Liang Lei sale of electricity companies
Equally possess powerful competitiveness.
Mainly in single or few aspect of sale of electricity company, these researchs are main to be concentrated for the research of Most current
It is also less to the research for influencing sale of electricity company competitiveness in terms of the price strategy of sale of electricity company and risk management, it is existing to comment
Valence system is not comprehensive.On the other hand, extremely lack for the sale of electricity company research under Power Market In China reform background.With electricity
How the progress changed, sale of electricity competition find the positioning of oneself for sale of electricity enterprise in sale of electricity specialization,
This is the strategic issue for having to face and following challenge.Therefore, it is highly desirable to combine the status of Chinese sale of electricity company, it is whole
A set of feasible appraisement system is managed, the development potentiality evaluation of sale of electricity company is used for and is excavated, more efficiently to promote to look forward to
The development of industry.
A kind of more perfect System of Comprehensive Evaluation thus is needed, it is public to independent sale of electricity by reasonable effective method
Department carries out evaluation sequence, excavates the development potentiality of independent sale of electricity company, finds the short slab of enterprise, provides and builds for the development of enterprise
View.
Summary of the invention
The problem of according to mentioning in background technique, the invention discloses a kind of, and the independent sale of electricity based on grey Cluster Evaluation is public
Take charge of development potentiality evaluation method characterized by comprising
Step 1 determines evaluation object；
Step 2 determines evaluation index according to the data of acquisition；
Step 3 establishes assessment indicator system；
Step 4, index cluster, using Grey Correlation Cluster, analyze the index in index system, and to index body
Index in system is deleted；
Step 5, the sale of electricity development of company Potential Evaluation model based on endpoint triangle albefaction power and the index system after deleting
The development potentiality of independent sale of electricity company is evaluated.
Specific step is as follows for Grey Correlation Cluster in the step 4:
The number of independent sale of electricity company to be evaluated in step 41, assessment indicator system is n, each independent sale of electricity company
In have m evaluation index characteristic, it is as follows to obtain sequence:
X1=(x1(1),x1(2),…,x1(n))
X2=(x2(1),x2(2) ..., x2(n))
Xm=(xm(1),xm(2),…,xm(n))
Step 42: sequence of calculation initial point pulverised picture
To two systems behavior sequence Xi=(xi(1),xi(2),…,xi(n)), i=1,2 ..., m and Xj=(xj(1),xj
(2),…,xj(n)), j=1,2 ... m calculate separately its initial point pulverised picture
In formulaWithRespectively sequence XiAnd XjInitial point pulverised as sequence；
Step 43: the sequence of calculationWithIntegral
S in formulaiAnd sjRespectively sequenceWithIntegral；
Step 44: the sequence of calculationWithThe integral of difference
Step 45: sequence of calculation XiAnd XjGrey absolute correlation degree
ε in formulaijFor sequence XiAnd XjGrey absolute correlation degree；
Step 46: to all i≤j, calculating XiWith XjGrey absolute correlation degree εij, obtain upper triangular matrix
ε in formulaii=1, i=1,2 ..., m, j=1,2 ..., m, A are characterized variable association matrix；
It takes and determines critical value r ∈ [0,1], work as εij>=r and when i ≠ j, then regard XiWith XjFor homogenous characteristics；
After grey cluster, l evaluation index of assessment indicator system residue.
The specific steps of sale of electricity development of company Potential Evaluation model based on endpoint triangle albefaction power in the step 5 are such as
Under:
Step 51: grey class number z is divided needed for requiring according to assessment, also correspondingly by jth ' a evaluation index value range
It is divided into z minizone:
[a1,a2],…,[ak-1,ak],…,[az-1,az],[az,az+1]
Wherein akValue generally can according to actual assessment require or qualitative research result determine, j '=1,2 ..., l, l be refer to
Mark system deletes rear remaining index number, k=1,2 ... z, z+1；
Step 52: determining and minizone [a1,a2] and minizone [az,az+1] corresponding grey class 1 and grey class z turning pointThe set midpoint of each minizone, λ are calculated simultaneouslyk=(ak+ak+1)/2, k=1,2 ... z；
Step 53: for grey class 1 and grey class z, constructing corresponding lower limit and estimate whitened weight functionWith
Upper measure whitened weight function
If x is an observation of index j ', whenOrWhen, by formula
Or
Calculate its value about grey class 1 and grey class zOr
Step 54: for grey class k；Tie point simultaneouslyWith the geometry midpoint of grey class k-1Or grey class 1
Turning pointAndWith the geometry midpoint of grey class k+1Or the turning point of grey class 1?
Triangle whitened weight function to evaluation index j ' about grey class k
For an observation x of evaluation index j ', its value for belonging to grey class k is calculated by following formula
Step 55: the weights omega of each index is determined using expert gradedj′；
Step 56: calculating synthetic clustering coefficient of g-th of sale of electricity company about grey class k
WhereinFor the whitened weight function of evaluation index j ' subclass k, ωj′For power of the index j in comprehensive cluster
Weight, g=1,2 ... n, k=1,2 ..., z；
Step 57: byJudge that sale of electricity company g belongs to grey class k*；When calculating all sale of electricity companies
After the grey class belonged to, the grey class belonged to according to each sale of electricity company is ranked up all sale of electricity companies；
When there is multiple sale of electricity companies to belong to kth*When grey class, according to synthetic clustering coefficientSize determination belong to k*
The superiority and inferiority or precedence of each object in grey class.
It is divided into the step 55:
Step 551 is assumed to share t experts, asks each expert to give a mark each index importance, obtain each evaluation
The score of index importance；
Step 552 is compared analysis to the marking result of each expert again, and analysis result is fed back to t experts,
Second is carried out to give a mark；
Next step 553 repeats step 551 and step 552, until the result of expert estimation no longer changes；
Step 554, the average for calculating each evaluation index
In formulaIt is jth ' a evaluation index average, j '=1,2 ..., l；ui′j′Indicate the i-th ' a expert to the
The marking of a evaluation index of j ', i '=1,2 ..., t；
Step 555, the weight for calculating each evaluation index
ω in formulaj′It is jth ' a evaluation index weight.
The invention has the benefit that
(1) present invention establishes development potentiality overall merit in terms of macro environment and independent sale of electricity company micro and refers to
Mark system, the system are capable of the difference and strengths and weaknesses of comprehensively more each sale of electricity company, for the development for excavating independent sale of electricity company
Potentiality lay the foundation.
(2) use Grey Correlation Cluster model simplification index system, the difficulty of data collection and processing can be reduced, for into
The evaluation of a large amount of independent sale of electricity companies of row improves efficiency.
(3) using the independent sale of electricity development of company Potential Evaluation model weighed based on endpoint triangle albefaction, simple, knot is calculated
Fruit is clear, is able to carry out the comparison of multiple sale of electricity companies, finds the potentiality of different sale of electricity companies, advised according to result.
Detailed description of the invention
Fig. 1 is in a kind of independent sale of electricity development of company Assessment Method on Potential embodiment based on grey Cluster Evaluation of the present invention
The relational graph of independent sale of electricity company evaluation index system.
Specific embodiment
The embodiment of the present invention is specifically addressed with reference to the accompanying drawing,
The embodiment of the present invention the following steps are included:
Step 1 determines evaluation object
Independent sale of electricity company refers to the sale of electricity company that non-governmental capital is set up, and the present invention can be used for the evaluation of multiple objects.
Step 2, data analysis
Evaluation index is determined according to the data that can be obtained.According to sale of electricity company entry criteria, sale of electricity company needs pair
Asset request, practitioner, management place and equipment, credit request etc. carry out publicity.Therefore, the sale of electricity company that can be obtained
Data include:
Registered capital and electricity sales amount scale
According to the rules, sale of electricity corporate assets total value should be not less than 20,000,000.When sale of electricity register of company fund is 2,000 ten thousand to 1
At hundred million yuans, year, electricity sales amount was between 600,000,000 to 3,000,000,000 kilowatt hours；Registered capital at 100,000,000 to 200,000,000 yuans, sell by year
Electricity is between 3,000,000,000 to 6,000,000,000 kilowatt hours；At 200,000,000 yuans of registered capital or more, its electricity sales amount is not limited.
Practitioner
Sale of electricity company should possess 10 and above professional, grasp electric system basic fundamental, economics are known
Know, has the abilities such as electric energy management, administration of energy conservation, demand side management, there is 3 years and the above working experience.Wherein to practitioner
Requirement be to have a high title, the managerial personnel of Sanming City intermediate title and six common employees.
Management place and equipment
Sale of electricity company should have the fixation management place being adapted with sale of electricity scale and technical support system for power market
The information system and client service platform needed can satisfy and participate in the quotation of marketing, information is reported and submitted, contract signing and visitor
The functions such as family service.
Credit request
Sale of electricity company should be without bad credit record, and requires to make credit promise according to the rules, it is ensured that honest operation.
In addition to sale of electricity company oneself factor, locating for external environment be also influence its development an important factor for.It can obtain
The external data taken includes:
Economic development data
Economic development data mainly include that regional production total value (refers to that a country ownership resident unit gives birth to over a period to come
Produce movable end result), each industry output total value, each industry is to the contribution rate of economic development and pulling function etc..
Energy-consuming data
Energy-consuming data refer mainly to whole society's electricity consumption situation, specifically include the Analyzing Total Electricity Consumption and not of Different Industries
Analyzing Total Electricity Consumption data of the same trade.
Power market transaction data
According to the electricity transaction data that power exchange is announced, it can obtain and hand in monthly sale of electricity company, season or year
Easy total electricity, different sales of electricity company conclusion of the business electricity account for the ratio of total volume, long-term agreement conclusion of the business electricity and long association's conclusion of the business electricity
The ratio of assembly alternating current amount, estimated year electricity sales amount, practical electricity sales amount and it is expected that electricity sales amount deviation ratio etc..
Step 3 establishes assessment indicator system
Assessment indicator system is determined according to the data that can be obtained；As shown in Fig. 1, each index is explained as follows table institute
Show.
The independent sale of electricity development of company Potential evaluation index of table 1 is explained
Step 4, index cluster
Grey Correlation Cluster is mainly used for the merger of similar factor, so that complication system simplifies.By Grey Correlation Cluster,
Whether we can investigate in many factors has several factors generally to belong to same class, us is enable to use these factors
Comprehensive average index or in which some make information not by heavy losses because usually representing this several factor.This belongs to
System variable deletes problem.Before carrying out large area investigation, by the Grey Correlation Cluster of typical sampling data, it can subtract
The collection of few unnecessary data, saves time and funds.
Using Grey Correlation Cluster, the index in step 3 is analyzed, to delete part index number.
Specific step is as follows for Grey Correlation Cluster model in step 4:
The number of independent sale of electricity company to be evaluated in step 41, assessment indicator system is n, in each independent sale of electricity company
There is m evaluation index characteristic, it is as follows to obtain sequence:
X1=(x1(1),x1(2),…,x1(n))
X2=(x2(1),x2(2),…,x2(n))
Xm=(xm(1),xm(2),…,xm(n))
8 sale of electricity companies to be evaluated are provided in the present embodiment, there are 18 evaluation index spies in each independent sale of electricity company
Levy data, n=8, m=18；It is as shown in table 2 to have volume representation:
The independent sale of electricity company evaluation achievement data of table 2
Step 42: sequence of calculation initial point pulverised picture
To two systems behavior sequence Xi=(xi(1),xi(2),…,xi(n)), i=1,2 ..., m and Xj=(xj(1),xj
(2),…,xj(n)), j=1,2 ... m calculate separately its initial point pulverised picture
In formulaWithRespectively sequence XiAnd XjInitial point pulverised as sequence.
Step 43: the sequence of calculationWithIntegral
S in formulaiAnd sjRespectively sequenceWithIntegral.
Step 44: the sequence of calculationWithThe integral of difference
Step 45: sequence of calculation XiAnd XjGrey absolute correlation degree
ε in formulaijFor sequence XiAnd XjGrey absolute correlation degree.
Step 46: to all i≤j, i, j=1,2 ..., m calculates XiWith XjGrey absolute correlation degree εij, obtain
Upper triangular matrix
ε in formulaii=1, i=1,2 ..., m, A are characterized variable association matrix.
It takes and determines critical value r ∈ [0,1], generally require r > 0.5, work as εijWhen >=r (i ≠ j), then X is regardediWith XjFor similar spy
Sign.R can according to practical problem it needs to be determined that, r classifies thinner closer to 1, and the variable in each grouping is relatively few；Point
Class is thicker, this is that variable in each grouping is relatively more.
Assuming that after grey cluster, l evaluation index of assessment indicator system residue.
In the present embodiment, clustering is carried out to index using the Data Data in above step and table 2, to all
I≤j, i, j=1,2 ..., 18, calculate XiWith XjGrey absolute correlation degree, obtain upper triangular matrix, enable r=0.80, choose
ε greater than 0.80ij, then have:
ε1,2=1.00, ε1,5=0.94, ε1,6=0.98, ε1,7=0.86, ε1,8=0.96, ε1,12=1.00, ε1,13=
1.00,
ε2,5=0.94, ε2,6=0.99, ε2,7=0.86, ε2,8=0.96, ε2,12=1.00, ε2,13=1.00,
ε4,14=0.90, ε4,15=0.90, ε4,17=0.98, ε5,6=0.93, ε5,7=0.83, ε5,8=0.91, ε5,12=
0.94,ε5,13=0.94,
ε6,7=0.87, ε6.8=0.98, ε6,12=0.98, ε6,13=0.98, ε7,8=0.89, ε7,12=0.85, ε7,13=
0.85,
ε8,12=0.96, ε8,13=0.96, ε10,16=0.81, ε11,18=0.90, ε12,13=1.00, ε14,15=1.00,
ε14,17=0.88, ε15,17=0.89
To known to: I1,I2,I5,I6,I7,I8,I12And I13In same class, the referred to as first kind；I4,I14,I15And I17?
In same class, referred to as the second class；I10And I16In same class, referred to as third class；I11And I18It is known as the 4th class in same class.
In the present embodiment, become in the first kind including economic trend, Tertiary Industy Development trend, region electricity consumption
Gesture, tertiary industry electricity consumption trend, power market transaction trend, independent sale of electricity company overall development status, credit situation and
Information announcing situation index, for reflecting Macro-external environment locating for sale of electricity company, including economy, energy-consuming status and city
The index of field race condition and independent sale of electricity company credit situation；Second category include independent sale of electricity company, former years transaction at
Alternating current amount, former years long-term agreement exchange hand and deviation ratio index, for reflecting the operation ability of independent sale of electricity power；In third class
Including the sale of electricity company sale of electricity scale upper limit and it is expected that year sale of electricity figureofmerit, reflects the sale of electricity scale of independent sale of electricity company；4th class
Including practitioner's situation and sale of electricity corporate scope index, reflect that human resources and business scope send out independent sale of electricity company
Open up the influence of potentiality.
In order to simplify evaluation evaluation index, continue that 9 evaluation indexes is selected to carry out independent sale of electricity company in the present embodiment
Development potentiality evaluation.It wherein include economic trend, Tertiary Industy Development trend and region electricity consumption trend in the first kind
Three evaluation indexes, the second class include independent sale of electricity company, former years transaction conclusion of the business electricity and former years long-term agreement conclusion of the business electricity three
A evaluation index, third class include one evaluation index of estimated year electricity sales amount, and the 4th class includes that practitioner's situation and sale of electricity are public
Take charge of two evaluation indexes of business scope.
Step 5 determines evaluation method
Development using the sale of electricity development of company Potential Evaluation model weighed based on endpoint triangle albefaction to independent sale of electricity company
Potentiality are evaluated, and wherein evaluation index is the index screened in step 4 through Grey Correlation Cluster.Grey based on mixing endpoint
Triangle whitened weight function is suitable for each grey class sharpness of border, but the situation that the point that may belong to different each grey classes is unknown.
Specific step is as follows for sale of electricity development of company Potential Evaluation model based on endpoint triangle albefaction power in step 5:
Step 51: the grey class number z divided needed for being required according to assessment, also correspondingly by the value range of each evaluation index
It is divided into z grey class, such as by jth ' a evaluation index value range [a1,az+1] it is divided into z minizone:
[a1,a2],…,[ak-1,ak],…,[az-1,az],[az,az+1]
Wherein akThe value of (k=1,2 ... z, z+1) can generally be required according to actual assessment or qualitative research result determines, j '
=1,2 ..., l.
Step 52: determining and [a1,a2] and [az,az+1] corresponding grey class 1 and grey class z turning pointIt counts simultaneously
Calculate the set midpoint of each minizone, λk=(ak+ak+1)/2, k=1,2 ... z.
Step 53: for grey class 1 and grey class z, constructing corresponding lower limit and estimate whitened weight functionWith
Upper measure whitened weight function
If x is an observation of index j ', whenOrWhen, it can be respectively by formula
Or
Calculate its value about grey class 1 and grey class zOr
Step 54: for grey class k, while tie pointWith the geometry midpoint of grey class k-1(or grey class 1
Turning point) andWith the geometry midpoint of grey class k+1(or the turning point of grey class 1),
Obtain triangle whitened weight function of the j ' index about grey class k
For an observation x of index j ', its value for belonging to grey class k can be calculated by following formula
Step 55: determining the weights omega of each indexj′, j=1,2 ..., l；Referred in the present embodiment using expert graded determination
Mark weight.
Assuming that sharing t experts, asks each expert to give a mark each index importance, it is important to obtain each evaluation index
The score of property；Then, analysis is compared to the marking result of each expert, and analysis result is fed back into t experts, carried out
Second of marking；Next above two step is repeated, until the result of expert estimation no longer changes.
The average of each evaluation index is calculated first
In formulaIt is jth ' a evaluation index average, j '=1,2 ..., l；ui′j′Indicate the i-th ' a expert to the
The marking of a evaluation index of j ', i '=1,2 ..., t.
Then the weight of each evaluation index is calculated
ω in formulaj′It is jth ' a evaluation index weight.
Step 56: calculating synthetic clustering coefficient of g-th of sale of electricity company about grey class k
WhereinFor j ' index k subclass whitened weight function, ωj′For weight of the index j in comprehensive cluster, g=1,
2 ... n, k=1,2 ..., z.
Step 57: byJudge that sale of electricity company g belongs to grey class k*；When there is multiple sale of electricity companies to belong to
In kth*When grey class, according to synthetic clustering coefficientSize determination belong to k*The superiority and inferiority or precedence of each object in grey class.
In the present embodiment, the development potentiality of 8 independent sale of electricity companies is evaluated in steps of 5, determines excellent middle difference
9 evaluation indexes, i.e., be divided into 4 grades by four grey classes；The value range of each evaluation index is evenly divided into four
Minizone；Then the turning point of each grey class is determined according to the section of delimitation, i.e., thus the set midpoint of each minizone is distinguished
It is as follows to establish whitened weight function:
Then the value of ash class described in each index is calculated.By taking company A as an example, calculated result is as shown in table 3.
Each index ash class value calculated result of table 3A company
| Index | It is excellent | It is good | In | Difference |
| I1 | 0.0000 | 0.8498 | 0.1502 | 0.0000 |
| I2 | 0.0000 | 0.3124 | 0.6876 | 0.0000 |
| I4 | 0.0000 | 0.0000 | 0.8123 | 0.1877 |
| I5 | 0.0000 | 0.0000 | 0.4005 | 0.5995 |
| I11 | 1.0000 | 0.0000 | 0.0000 | 0.0000 |
| I14 | 0.0000 | 0.0000 | 0.7737 | 0.2263 |
| I15 | 0.0000 | 0.0000 | 0.7277 | 0.2723 |
| I16 | 0.6172 | 0.3828 | 0.0000 | 0.0000 |
| I18 | 1.0000 | 0.0000 | 0.0000 | 0.0000 |
It determines index weights, and calculates synthetic clustering coefficient.Invite the expert in three sale of electricity fields by marking, by most
Average afterwards determines index weights, last weight are as follows: 0.1119,0.0979,0.1259,0.1259,0.1189,
0.1119,0.0979,0.0839,0.1259. is calculated synthetic clustering coefficient, as shown in table 4:
4 synthetic clustering coefficient of table
| Grey class | A1 | A2 | A3 | A4 | A5 | A6 | A7 | A8 |
| It is excellent | 0.2966 | 0.4313 | 0.4130 | 0.1196 | 0.3977 | 0.2098 | 0.4625 | 0.4489 |
| It is good | 0.1578 | 0.3386 | 0.1841 | 0.4197 | 0.1750 | 0.0191 | 0.0830 | 0.0711 |
| In | 0.3946 | 0.1992 | 0.3127 | 0.2236 | 0.2888 | 0.5505 | 0.3082 | 0.2725 |
| Difference | 0.1511 | 0.0309 | 0.0902 | 0.2371 | 0.1386 | 0.2206 | 0.1463 | 0.2076 |
It can be seen from the results that rating level has 5 for excellent, respectively in eight independent sale of electricity companies being evaluated
For A2, A3, A5, A7, A8；Opinion rating has 1 for good, is A4；It is A1 and A6 there are two being evaluated as.On the whole,
In eight independent sale of electricity companies, overall order of quality are as follows: A7 > A8 > A2 > A3 > A5 > A4 > A6 > A1.
Claims (4)
1. a kind of independent sale of electricity development of company Assessment Method on Potential based on grey Cluster Evaluation characterized by comprising
Step 1 determines evaluation object；
Step 2 determines evaluation index according to the data of acquisition；
Step 3 establishes assessment indicator system；
Step 4, index cluster, using Grey Correlation Cluster, analyze the index in index system, and in index system
Index deleted；
Step 5, the sale of electricity development of company Potential Evaluation model based on endpoint triangle albefaction power and the index system after deleting are to only
The development potentiality of vertical sale of electricity company is evaluated.
2. a kind of independent sale of electricity development of company Assessment Method on Potential based on grey Cluster Evaluation according to claim 1,
It is characterized in that, specific step is as follows for Grey Correlation Cluster in the step 4:
The number of independent sale of electricity company to be evaluated in step 41, assessment indicator system is n, has m in each independent sale of electricity company
A evaluation index characteristic, it is as follows to obtain sequence:
X1=(x1(1),x1(2),…,x1(n))
X2=(x2(1),x2(2),…,x2(n))
Xm=(xm(1),xm(2),…,xm(n))
Step 42: sequence of calculation initial point pulverised picture
To two systems behavior sequence Xi=(xi(1),xi(2),…,xi(n)), i=1,2 ..., m and Xj=(xj(1),xj
(2),…,xj(n)), j=1,2 ... m calculate separately its initial point pulverised picture
In formulaWithRespectively sequence XiAnd XjInitial point pulverised as sequence；
Step 43: the sequence of calculationWithIntegral
S in formulaiAnd sjRespectively sequenceWithIntegral；
Step 44: the sequence of calculationWithThe integral of difference
Step 45: sequence of calculation XiAnd XjGrey absolute correlation degree
ε in formulaijFor sequence XiAnd XjGrey absolute correlation degree；
Step 46: to all i≤j, calculating XiWith XjGrey absolute correlation degree εij, obtain upper triangular matrix
ε in formulaii=1, i=1,2 ..., m, j=1,2 ..., m, A are characterized variable association matrix；
It takes and determines critical value r ∈ [0,1], work as εij>=r and when i ≠ j, then regard XiWith XjFor homogenous characteristics；
After grey cluster, l evaluation index of assessment indicator system residue.
3. a kind of independent sale of electricity development of company Assessment Method on Potential based on grey Cluster Evaluation according to claim 1,
It is characterized in that, the specific steps of the sale of electricity development of company Potential Evaluation model based on endpoint triangle albefaction power in the step 5
It is as follows:
Step 51: dividing grey class number z needed for requiring according to assessment, jth ' a evaluation index value range is also correspondingly divided
For z minizone:
[a1,a2],…,[ak-1,ak],…,[az-1,az],[az,az+1]
Wherein akValue generally can according to actual assessment require or qualitative research result determine, j '=1,2 ..., l, l be index body
Rear remaining index number, k=1,2 ... z, z+1 delete in system；
Step 52: determining and minizone [a1,a2] and minizone [az,az+1] corresponding grey class 1 and grey class z turning pointThe set midpoint of each minizone, λ are calculated simultaneouslyk=(ak+ak+1)/2, k=1,2 ... z；
Step 53: for grey class 1 and grey class z, constructing corresponding lower limit and estimate whitened weight functionAnd the upper limit
Estimate whitened weight function
If x is an observation of index j ', whenOrWhen, by formula
Or
Calculate its value about grey class 1 and grey class zOr
Step 54: for grey class k；Tie point simultaneouslyWith the geometry midpoint of grey class k-1Or the turnover of grey class 1
PointAndWith the geometry midpoint of grey class k+1Or the turning point of grey class 1It is commented
Triangle whitened weight function of the valence index j ' about grey class kJ '=1,2 ..., l；K=2,3 ...,
z-1；
For an observation x of evaluation index j ', its value for belonging to grey class k is calculated by following formulaK=1,2 ... z；
Step 55: the weights omega of each index is determined using expert gradedj′；
Step 56: calculating synthetic clustering coefficient of g-th of sale of electricity company about grey class k
WhereinFor the whitened weight function of evaluation index j ' subclass k, ωj′For weight of the index j in comprehensive cluster, g=
1,2 ... n, n are the number of independent sale of electricity company to be evaluated, k=1,2 ..., z；
Step 57: byJudge that sale of electricity company g belongs to grey class k*；When calculating what all sale of electricity companies belonged to
After grey class, the grey class belonged to according to each sale of electricity company is ranked up all sale of electricity companies；
When there is multiple sale of electricity companies to belong to kth*When grey class, according to synthetic clustering coefficientSize determination belong to k*Grey class
The superiority and inferiority or precedence of middle each object.
4. a kind of independent sale of electricity development of company Assessment Method on Potential based on grey Cluster Evaluation according to claim 3,
It is characterized in that, being divided into the step 55:
Step 551 is assumed to share t experts, asks each expert to give a mark each index importance, obtain each evaluation index
The score of importance；
Step 552 is compared analysis to the marking result of each expert again, and analysis result is fed back to t experts, carries out
Second of marking；
Next step 553 repeats step 551 and step 552, until the result of expert estimation no longer changes；
Step 554, the average for calculating each evaluation index
In formulaIt is jth ' a evaluation index average, j '=1,2 ..., l；ui′j′Indicate the i-th ' a expert to jth ' a
The marking of evaluation index, i '=1,2 ..., t；
Step 555, the weight for calculating each evaluation index
ω in formulaj′It is jth ' a evaluation index weight.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112926816A (en) * | 2020-09-08 | 2021-06-08 | 广东电网有限责任公司 | Supplier evaluation method, supplier evaluation device, computer equipment and storage medium |
| CN113127606A (en) * | 2021-06-18 | 2021-07-16 | 西南交通大学 | Construction behavior safety risk analysis and dangerous point identification method based on knowledge graph |
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2018
- 2018-07-30 CN CN201810852516.7A patent/CN109146259A/en active Pending
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| 刘思峰: "两阶段灰色综合测度决策模型与三角白化权函数的改进", 《控制决策》 * |
| 尤艳伟: "辽宁装备制造企业国际竞争力研究", 《中国优秀硕士学位论文全文数据库经济与管理科学辑》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112926816A (en) * | 2020-09-08 | 2021-06-08 | 广东电网有限责任公司 | Supplier evaluation method, supplier evaluation device, computer equipment and storage medium |
| CN112926816B (en) * | 2020-09-08 | 2023-09-22 | 广东电网有限责任公司 | Vendor evaluation method, device, computer device and storage medium |
| CN113127606A (en) * | 2021-06-18 | 2021-07-16 | 西南交通大学 | Construction behavior safety risk analysis and dangerous point identification method based on knowledge graph |
| CN113127606B (en) * | 2021-06-18 | 2021-08-31 | 西南交通大学 | Construction behavior safety risk analysis and dangerous point identification method based on knowledge graph |
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