CN109377062A - A kind of oil field Service Component evaluation method based on improvement entropy weight gray relative analysis method - Google Patents
A kind of oil field Service Component evaluation method based on improvement entropy weight gray relative analysis method Download PDFInfo
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Abstract
It is specifically a kind of based on the oil field Service Component evaluation method for improving entropy weight gray relative analysis method the invention belongs to Comprehensive Assessment Technology field.The following steps are included: A. collects the usage log of oil field Service Component, simultaneously statistical correlation Service Component information is filtered to log content, therefrom chooses evaluation index；B. according to the evaluation index data of each oil field Service Component, evaluations matrix is established；C. according to the attribute type of each evaluation index, different methods is selected to standardize, former evaluations matrix is converted to standardization evaluations matrix；D. it is calculated using Information Entropy, obtains the objective weight of each evaluation index；E. by changing calculation of relationship degree formula improved grey relational analysis method, and index weights information is combined, constructs comprehensive evaluation model；F. comprehensive evaluation model is utilized, oil field Service Component is evaluated, obtains evaluation seniority among brothers and sisters.The present invention merges Information Entropy and gray relative analysis method, have the advantages that evaluation result is objective, sample require it is few, it can be used for the evaluation of oil field Service Component, realize the measurable of oil field Service Component evaluation, provide important references to choose high-quality oil field Service Component.
Description
Technical field
The invention belongs to Comprehensive Assessment Technology field, it can be used for realizing measurable, the preferred oil of oil field Service Component evaluation
Field Service Component, it is specifically a kind of based on the oil field Service Component evaluation method for improving entropy weight gray relative analysis method.
Background technique
With the continuous development of computer technology, the environment that modern oilfield enterprise faces becomes increasingly complex, information system
Most of is multi-platform, multisystem complication system.This requires under Internet environment, realization system be loose coupling,
It is cross-platform, unrelated with language, unrelated with special interface, and the reliable access to application program to be provided.
The appearance of service has brought pleasantly surprised, and this technology can operate mutually in different operating environments, disappear
Except huge information island, information sharing is realized, carry out data exchange, reach the consistency of information.With the day of service technology
Become mature, the Service Instance on network with function of the same race is also more and more, and applicability is used in enterprise and business application
Low service will lead to the inefficiency entirely applied, and error rate is high, or even application is terminated and executed.Therefore it needs to comment by service
Valence technology carrys out the quality of quantification service, provides foundation to choose good service automatically and screening out service inferior.
Traditional service evaluation method mainly by testing service quality, provides description quality of service characteristics (such as
Runing time, operating cost etc.) evaluation of estimate, traditional service evaluation method is due to needing to the internal information and code of service
It accesses, the considerations of for safety and commercial interest, implements certain difficulty, and can not embody user's
Individual demand or preference.Modern evaluation algorithms mainly have levels analytic approach, fuzzy comprehensive evaluation method, DEA Method,
Evaluation Using Artificial Neural Network method etc., above-mentioned various methods all achieve certain success in practical applications, but all there is its office
It is sex-limited, thus often integrate in practical applications several algorithms building comprehensive evaluation models come using.
Research at present for the evaluation of oil field business is less, lacks a kind of scientific and reasonable evaluation method, and the present invention provides
It is a kind of based on the integrated evaluating method for improving entropy weight gray relative analysis method, made using the information used in connection with of Service Component
For evaluation index, it can more embody user and really be actually needed, so that evaluation result is partial to user demand, to improve evaluation
Accuracy reinforces the management of oil field Service Component, preferably Service Component to oilfield enterprise, and improving service quality all has important meaning
Justice, while directive function also is played to the selection and combination of oil field Service Component.
Summary of the invention
The purpose of the present invention is providing a kind of scientific and rational integrated evaluating method for oil field Service Component, oil field is realized
Service Component is evaluated measurable, provides scientific basis for preferred oil field Service Component.
Based on the oil field Service Component evaluation method for improving entropy weight gray relative analysis method, comprising the following steps:
A. from the Service Component log of oil field statistical service component indication information, and determine evaluation indice T={ a1,
a2,…,an}；
B. according to the achievement data of each Service Component, evaluations matrix A=(a is establishedij)m×n, wherein m is business to be evaluated
Number of components, n are the evaluation index number of Service Component；
C. two classes, positive evaluation index and reverse evaluation index are divided into according to the type difference of evaluation index, to inhomogeneity
The evaluation index of type carries out standardization processing with different methods, converts standardization evaluations matrix X for iotave evaluation matrix A
=(xij)m×n, different types of normalization method is as follows:
(1) positive evaluation index normalization method
Positive evaluation index is the evaluation index that index value is the bigger the better, and normalizing is as follows:
(2) reverse evaluation index normalization method
Reverse evaluation index is the smaller the better evaluation index of index value, and normalizing is as follows:
D. the characteristic that can reflect data discrete degree using entropy, obtains the objective weight of each evaluation index using Information Entropy
E. comprehensive evaluation model, I={ 1,2 ..., m }, J={ 1,2 ..., n } are constructed
(1) from standardization evaluations matrix X, select each evaluation index optimal value, constitute reference sequences y, remaining as than
Compared with sequence, the incidence coefficient matrix R=(r for comparing sequence and reference sequences is calculated using gray relative analysis methodij)m×n:
xi(k) as follows with the calculation formula of the incidence coefficient of y (k)
Wherein ρ is known as resolution ratio, and for indicating the size of resolution capability, the value between section (0,1) commonly uses value
It is 0.5；
(2) from incidence coefficient matrix R=(rij)m×nMiddle determining ideal column η+With negative ideal column η-
(3) each incidence coefficient sequence and ideal column η are calculated separately+, negative ideal column η-Between weighted euclidean distance
(4) new degree of association γ is calculated as evaluation score
F. the evaluation index data of oil field Service Component are brought into comprehensive evaluation model and are calculated, obtained overall merit and obtain
Point, score value is higher, and expression Service Component is better.
Detailed description of the invention
Fig. 1 is the flow chart of oil field Service Component evaluation method.
Specific embodiment
The present invention is described in further detail with example with reference to the accompanying drawing, but embodiments of the present invention not office
It is limited to the range of example expression.
Step 1: process, the first Criterion Attribute of statistics oil field Service Component, and determining evaluation index according to Fig. 1,
Following data is provided in example:
Step 2: establishing evaluations matrix A=(a according to the achievement data of each oil field Service Componentij)6×3:
Step 3: analyzing each evaluation index attribute, amount of access, application range and user's evaluation generally require to be the bigger the better,
I.e. positive index.Original matrix A is converted into standardization evaluations matrix X.Generalized method is returned using formula 1, standardization is obtained and comments
Valence matrix X=(xij)6×3:
Step 4: obtain the objective weight of each evaluation index using Information Entropy method, then amount of access, application range and use
The objective weight of family evaluation are as follows: W=(0.68,0.30,0.02).
Step 5: determining reference sequences y={ 1.00,1.00,1.00 }, ρ takes 0.5 in formula 3, and incidence coefficient is calculated
Matrix R=(rij)6×3:
Step 6: determining incidence coefficient ideal column η+={ 1.00,1.00,1.00 } and negative ideal column η-=0.33,0.38,
0.54 }, weight W is calculated in the 5th step and brings formula 6 and formula 7 into, the d of each oil field Service Component is calculatedi +And di -,
The evaluation score γ of each oil field Service Component is finally calculated with formula 8i:
The indication information and ranking of each oil field Service Component are as shown in the table:
As seen from the above table, in this example oil field Service Component ranking are as follows: 2 > 1 > 3 > 5 > 6 > 10.
Claims (1)
1. it is a kind of based on improve entropy weight gray relative analysis method oil field Service Component evaluation method, which is characterized in that including with
Lower step:
A. from the Service Component log of oil field statistical service component indication information, and determine evaluation indice T={ a1,a2,…,
an}；
B. according to the achievement data of each Service Component, evaluations matrix A=(a is establishedij)m×n, wherein m is Service Component to be evaluated
Number, n are the evaluation index number of Service Component；
C. two classes, positive evaluation index and reverse evaluation index are divided into according to the type difference of evaluation index, to different types of
Evaluation index carries out standardization processing with different methods, converts standardization evaluations matrix X=for iotave evaluation matrix A
(xij)m×n, different types of normalization method is as follows:
(1) positive evaluation index normalization method
Positive evaluation index is the evaluation index that index value is the bigger the better, and normalizing is as follows:
(2) reverse evaluation index normalization method
Reverse evaluation index is the smaller the better evaluation index of index value, and normalizing is as follows:
D. the characteristic that can reflect data discrete degree using entropy, obtains the objective weight of each evaluation index using Information Entropy
E. comprehensive evaluation model, I={ 1,2 ..., m }, J={ 1,2 ..., n } are constructed
(1) from standardization evaluations matrix X, each evaluation index optimal value is selected, constitutes reference sequences y, remaining, which is used as, compares sequence
Column calculate the incidence coefficient matrix R=(r for comparing sequence and reference sequences using gray relative analysis methodij)m×n:
xi(k) as follows with the calculation formula of the incidence coefficient of y (k)
Wherein ρ is known as resolution ratio, and for indicating the size of resolution capability, the value between section (0,1), common value is
0.5；
(2) from incidence coefficient matrix R=(rij)m×nMiddle determining ideal column η+With negative ideal column η-
(3) each incidence coefficient sequence and ideal column η are calculated separately+, negative ideal column η-Between weighted euclidean distance
(4) new degree of association γ is calculated as evaluation score
F. the evaluation index data of oil field Service Component are brought into comprehensive evaluation model and are calculated, obtain overall merit score,
Score value is higher, and expression Service Component is better.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110210740A (en) * | 2019-05-22 | 2019-09-06 | 广西电网有限责任公司电力科学研究院 | A kind of distribution network reliability evaluation method considering power supply quality |
| CN110363432A (en) * | 2019-07-17 | 2019-10-22 | 国网河南省电力公司开封供电公司 | Based on improvement entropy weight-grey correlation distribution network reliability impact analysis method |
| CN110555624A (en) * | 2019-09-10 | 2019-12-10 | 合肥工业大学 | power grid dispatching operation comprehensive evaluation method considering index correlation |
| CN111881560A (en) * | 2020-07-08 | 2020-11-03 | 南京航空航天大学 | Machining parameter optimization method based on grey correlation analysis method-entropy weight ideal point method and machining surface integrity multi-index |
| CN112101649A (en) * | 2020-09-07 | 2020-12-18 | 南京航空航天大学 | Machining parameter optimization method based on fuzzy entropy weight comprehensive evaluation method-grey correlation analysis method and surface quality evaluation system |
| CN117541082A (en) * | 2024-01-05 | 2024-02-09 | 中国石油大学(华东) | Comprehensive evaluation method based on oil reservoir-shaft-equipment evaluation index integration |
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2018
- 2018-10-31 CN CN201811281911.0A patent/CN109377062A/en active Pending
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110210740A (en) * | 2019-05-22 | 2019-09-06 | 广西电网有限责任公司电力科学研究院 | A kind of distribution network reliability evaluation method considering power supply quality |
| CN110210740B (en) * | 2019-05-22 | 2023-09-15 | 广西电网有限责任公司电力科学研究院 | Power distribution network reliability assessment method considering power supply quality |
| CN110363432A (en) * | 2019-07-17 | 2019-10-22 | 国网河南省电力公司开封供电公司 | Based on improvement entropy weight-grey correlation distribution network reliability impact analysis method |
| CN110555624A (en) * | 2019-09-10 | 2019-12-10 | 合肥工业大学 | power grid dispatching operation comprehensive evaluation method considering index correlation |
| CN111881560A (en) * | 2020-07-08 | 2020-11-03 | 南京航空航天大学 | Machining parameter optimization method based on grey correlation analysis method-entropy weight ideal point method and machining surface integrity multi-index |
| CN111881560B (en) * | 2020-07-08 | 2024-05-17 | 南京航空航天大学 | Processing parameter optimization method based on gray correlation analysis method-entropy weight ideal point method and processing surface integrity multi-index |
| CN112101649A (en) * | 2020-09-07 | 2020-12-18 | 南京航空航天大学 | Machining parameter optimization method based on fuzzy entropy weight comprehensive evaluation method-grey correlation analysis method and surface quality evaluation system |
| CN112101649B (en) * | 2020-09-07 | 2023-10-10 | 南京航空航天大学 | Processing parameter optimization method based on fuzzy entropy weight comprehensive evaluation method-gray correlation analysis method and surface quality evaluation system |
| CN117541082A (en) * | 2024-01-05 | 2024-02-09 | 中国石油大学(华东) | Comprehensive evaluation method based on oil reservoir-shaft-equipment evaluation index integration |
| CN117541082B (en) * | 2024-01-05 | 2024-04-05 | 中国石油大学(华东) | Comprehensive evaluation method based on oil reservoir-shaft-equipment evaluation index integration |
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