CN116227972A - Scientific and technological attendant work quantitative evaluation method based on cloud platform - Google Patents
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Abstract
The invention discloses a cloud platform-based quantitative evaluation method for the work of a science and technology attendant, which comprises the following steps: s1, constructing an evaluation index system of a science and technology attendant, and carrying out standardized scoring on evaluation factors in the evaluation index system based on data of a cloud platform to obtain standardized scoring values of the evaluation factors; s2, determining the weight coefficient of the evaluation factor through an analytic hierarchy process and an entropy weight process, establishing a quantitative evaluation model of the work of the science and technology attendant, and establishing a science, practicality, emphasis ability, actual performance and contribution provincial personal science and technology attendant evaluation system on the basis of the cloud big data platform service of the science and technology attendant through the technical scheme of the invention, thereby providing a system guarantee for the structural optimization work of the science and technology attendant and effectively supporting the accuracy and scientificity of the evaluation of the related work of the provincial science and technology attendant.
Description
Technical Field
The invention relates to the technical field of agricultural production services, in particular to a cloud platform-based quantitative evaluation method for the work of a scientific and technological specialization staff.
Background
The technical and scientific attendant service cloud platform has the functions of online selection, knowledge service, demand release, achievement butt joint, interactive consultation, dynamic tracking, big data analysis and the like, realizes online application, assessment management, performance evaluation, dynamic service and remote service of the full-province technical and scientific and technological attendant, and is a comprehensive platform for the management and service of the full-province technical and technological attendant.
From the platform operation, a large amount of service record, work log, service track, achievement report and other related data of the science and technology attendant are generated, the past service quality is required to be evaluated nowadays, the related work evaluation of the science and technology attendant is accurately and scientifically supported, and the system guarantee is provided for the structure optimization work of the science and technology attendant.
Disclosure of Invention
Aiming at the problem that basis is not provided for quantitative assessment of the work of the technical and technical panelists at present, the invention provides a quantitative assessment method of the work of the technical and technical panelists based on a cloud platform.
A scientific and technological specialization staff work quantitative evaluation method based on a cloud platform comprises the following steps:
s1, constructing an evaluation index system of a science and technology attendant, and carrying out standardized scoring on evaluation factors in the evaluation index system based on data of a cloud platform to obtain standardized scoring values of the evaluation factors;
and S2, determining the weight coefficient of the evaluation factor through an analytic hierarchy process and an entropy weight process, and establishing a scientific and technological specialization staff work quantitative evaluation model.
Further, in the step S1, the evaluation latitudes are determined according to the requirements, and a first-level index is set under each evaluation latitude, wherein a second-level index is set under part of the first-level indexes, so that the construction of an evaluation index system is completed;
the evaluation factor includes a primary index and a secondary index.
Further, in the step S1, the performing normalized scoring on the evaluation factors in the evaluation index system based on the cloud platform data, to obtain normalized scoring values of the evaluation factors includes:
s101, carrying out quantization treatment on the evaluation factors by a positive factor quantization method and a negative factor quantization method to obtain quantization index coefficients;
s102, multiplying the quantization index coefficient by 100 to obtain a standardized grading value.
Further, in the step S101, the forward factor quantization method expression is:
wherein y is i A quantization index coefficient for the evaluation factor i; y is Y i A measurement value of the evaluation factor i; y is Y min Measuring a lower limit value for the evaluation factor i; y is Y max Upper limit measurement value for the evaluation factor i;
the negative evaluation factor quantification method expression is as follows:
wherein y is i A quantization index coefficient for the evaluation factor i; y is Y i A measurement value of the evaluation factor i; y is Y min Measuring a lower limit value for the evaluation factor i; y is Y max The upper limit measurement value of the evaluation factor i.
Further, in the step S2, determining the weight coefficient of the evaluation factor by the analytic hierarchy process includes the following steps:
s201, comparing the importance of n evaluation factors in pairs by adopting a 1-9 scale method to obtain a quantification result, and if the comparison value of the evaluation factor i relative to the evaluation factor j is b ij The comparison value of the evaluation factor j to the evaluation factor i is 1/b ij Establishing a judgment matrix B of n-order, wherein the expression is as follows:
s202, calculating a maximum characteristic root max lambda of the matrix B, and calculating a matrix consistency index CI:
if the CI value is smaller, the consistency of the matrix B is better, the consistency of the matrix B is checked by the matrix consistency ratio CR, and when CR is smaller than 0.1, the consistency of the matrix B is acceptable, step S203 is performed, where the expression of CR is:
wherein RI is a random consistency index.
S203, calculating a feature vector P= [ P ] corresponding to the maximum feature root max lambda 1 P 2 … P n ] T And carrying out normalization processing on the P to obtain a weight coefficient w of the evaluation factor.
Further, in the step S2, determining the weight coefficient of the evaluation factor by the entropy weight method includes the following steps:
s211, establishing an evaluation factor subdomain U= { U 1 ,u 2 ,…,u m Establishing an evaluation level domain v= { V }, which includes m evaluation factors 1 ,v 2 ,…,v n Establishing a fuzzy relation matrix X through U and V, wherein the expression is as follows:
wherein x is ij The value of the corresponding j-th evaluation factor in the i-th evaluation factors; when a certain evaluation factor x ij The larger the middle j is, the more important the evaluation factor is;
s212, calculating x ij The proportion of the evaluation level j corresponding to the i-th evaluation factor in the total number n of the evaluation levels is as follows:
s213, calculating information entropy of the j-th evaluation levelValue e j The calculation formula is as follows:
wherein, K is a constant,
y ij the quantized index coefficient of the evaluation factor corresponding to the j-th evaluation level;
information entropy e of evaluation factor j j The difference between the value of the information utility coefficient and 1 determines the value of the information utility coefficient of the evaluation factor, and the value of the information utility coefficient directly affects the weight, wherein the smaller the value of the information utility value is, the lower the importance of the corresponding evaluation factor is, the lower the weight coefficient of the evaluation factor is, and the information utility value coefficient d of the evaluation factor j is j The expression of (2) is:
d j ＝1-e j
s214, evaluating the information utility value coefficient d of the grade j j Calculating the weight coefficient of the evaluation level j, wherein the expression is as follows:
wherein w is j And (5) the weight coefficient corresponding to the j-th evaluation level.
Further, the expression of the quantitative evaluation model for the scientific and technological attendant works is as follows:
s is the total score of the work quantification of the science and technology attendant, namely the annual work performance total score of the science and technology attendant; w (w) i The weight coefficient is the evaluation factor; s is S i A normalized score value representing an evaluation factor; n is the number of evaluation factors.
Compared with the prior art, the invention has the advantages that: according to the technical scheme, on the basis of the cloud big data platform service of the science and technology attendant, a science, practicality, capability, actual performance and contribution provincial personal science and technology attendant assessment system is established, a system guarantee is provided for the structure optimization work of the science and technology attendant, and the accuracy and scientificity of the related work assessment of the provincial science and technology attendant are effectively supported.
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FIG. 1 is a schematic flow chart of the method of the present invention;
FIG. 2 is a block diagram of an evaluation index system of a scientific and technical attendant according to the present invention.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is only exemplary and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and/or the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.
Where expressions like at least one of "A, B and C, etc. are used, the expressions should generally be interpreted in accordance with the meaning as commonly understood by those skilled in the art (e.g.," a system having at least one of A, B and C "shall include, but not be limited to, a system having a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). Where a formulation similar to at least one of "A, B or C, etc." is used, in general such a formulation should be interpreted in accordance with the ordinary understanding of one skilled in the art (e.g. "a system with at least one of A, B or C" would include but not be limited to systems with a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
Some of the block diagrams and/or flowchart illustrations are shown in the figures. It will be understood that some blocks of the block diagrams and/or flowchart illustrations, or combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the instructions, when executed by the processor, create means for implementing the functions/acts specified in the block diagrams and/or flowchart. The techniques of this disclosure may be implemented in hardware and/or software (including firmware, microcode, etc.). Additionally, the techniques of this disclosure may take the form of a computer program product on a computer-readable storage medium having instructions stored thereon, the computer program product being for use by or in connection with an instruction execution system.
The data of the embodiment of the invention is from a cloud platform of a science and technology attendant in Fujian province, and the data span is three years 2019-2021. Data are largely divided into two categories: (1) scientific and technological attendant online service data; (2) The technical specializer work report data, specific sample size is shown in table 1. The number of online service persons accounts for nearly 1/3 of the ratio of the scientific and technological specialization staff, and the 2021 online ratio is reduced mainly due to the fact that the 2021 scientific and technological specialization staff has late choice, epidemic situation is eased, and offline service is high. The number of science and technology attendant reporting work has increased year by year, reaching 92.45% by 2021. Therefore, the data selected by the invention can cover most of data technology specializers, and has representativeness and authenticity.
TABLE 1 2019-2021 Tech Admission service instance sample size
A scientific and technological specialization staff work quantitative evaluation method based on a cloud platform comprises the following steps:
s1, constructing an evaluation index system of a science and technology attendant, and carrying out standardized scoring on evaluation factors in the evaluation index system based on data of a cloud platform to obtain standardized scoring values of the evaluation factors;
s2, determining the weight coefficient of the evaluation factor through an analytic hierarchy process and an entropy weight process, and establishing a scientific and technological attendant work quantitative evaluation model.
Currently, methods for determining weight coefficients can be largely classified into the following two types: objective weighting method and subjective weighting method, the former can well reflect subjective willingness of decision maker, but the evaluation result is easy to have considerable subjectivity, most classical as-generic analytic hierarchy process. The objective weight is determined by quantitative analysis method according to intrinsic factors of the index, and common methods include: neural network analysis, entropy analysis, principal component analysis, and the like. In practical application, the calculation mode of the weight coefficient needs to be rotated according to the data characteristics and requirements of different provinces, for example, at a certain evaluation latitude, subordinate evaluation factors of the evaluation latitude have a large amount of data, and the data are all changes of the workload of a science and technology attendant, so that the calculation of the weight coefficient of the evaluation factor can be performed through an entropy weight method; if a certain evaluation latitude has no data of subordinate evaluation factors, the entropy weight method is difficult to truly reflect the actual workload of a science and technology attendant, and the weight coefficient of the evaluation factors needs to be calculated by adopting the analytic hierarchy process.
Considering the characteristics of service and management of the scientific and technological specialities of Fujian province, the embodiment of the invention adopts a mode of combining a subjective and objective weighting method, adopts a combination of a hierarchical analysis method and an entropy value method, adopts the hierarchical analysis method to the evaluation latitude of the unobtainable data, and adopts the entropy weighting method to determine the weight coefficient of the rest part capable of acquiring the data. And calculating by utilizing MATLAB to obtain the weight coefficient of each evaluation factor of the scientific and technological specialization staff work quantitative evaluation index system based on the cloud platform.
Further, in step S1, evaluation latitudes are determined according to requirements, and a first-level index is set under each evaluation latitude, wherein a second-level index is set under part of the first-level indexes, so as to complete construction of an evaluation index system;
the evaluation factor includes a primary index and a secondary index.
And (3) constructing an evaluation index system:
the application of big data to evaluate the workload of science and technology specializers is a continuous and deepened process, and the rationality, the comprehensiveness and the scientificity of the selected indexes are key. Therefore, aiming at the service condition of provincial science and technology attendant and the condition of management workers, the selected index comprehensively considers the following principles:
(1) Integrity and layering principles: the basic conditions, work performance, social evaluation and the like are comprehensively considered by the science and technology attendant, so that the selected index has wide coverage, dynamic monitoring, multi-factor assessment, classification and layering management, group, personal and the like of the science and technology attendant are covered, and the work effect of the science and technology attendant service can be clearly achieved.
(2) Operability principle: the selected index should be easily measurable, data available, and sufficient consideration of the operability of the index should be required.
(3) Representative principle: the selected index has clear meaning, and in order to avoid redundancy of an index system, the selected index can reflect a key factor with a large influence or dominance on a certain aspect of a science and technology attendant, and no obvious correlation exists among the indexes.
(4) Dynamic principle: the purpose of the evaluation is to facilitate the realization of the management objective. Corresponding indexes are set in different stages of the development of things, so that the development of the scientific and technological specialization staff towards the expected targets is guided. Therefore, in setting the index, the emphasis and main tasks of the big data to enhance the service performance of the tech dispatcher in the current development stage need to be considered.
Screening of evaluation factors is carried out from four latitudes of government policy propaganda, science and technology propagation, innovation and innovation, and leading to enrichment, as shown in fig. 2.
Policy propaganda: setting four primary indexes including policy interpretation, policy propaganda, and satisfaction of management objects.
Science and technology propagation: the main investigation is that the performance of the scientific and technological attendant works sets eight primary indexes of on-site service, on-line service, scientific and technological training, release achievement, docking technology requirement, service main body number, popularization technology number and service object satisfaction.
Innovative creation: the method mainly refers to the achievement of a science and technology specifier as a pilot sheep of a science and technology innovation creation, and comprises four primary indexes of establishing a benefit community, creating the number of enterprises, setting up project items and establishing an demonstration base condition.
The belt head is rich: mainly refers to the index corresponding to the effect obtained by the science and technology specifier.
And a plurality of secondary indexes are also arranged below a part of the primary indexes, and are specifically set for the working evaluation standard of the scientific and technological specialities according to different provinces, wherein the primary indexes and the secondary indexes belong to evaluation factors, and each primary index and each secondary index have corresponding weight coefficients when corresponding weight coefficient calculation is carried out.
Further, in step S1, based on the data of the cloud platform, performing normalized scoring on the evaluation factors in the evaluation index system, where obtaining normalized scoring values of the evaluation factors includes:
s101, carrying out quantization treatment on the evaluation factors by a positive factor quantization method and a negative factor quantization method to obtain quantization index coefficients;
s102, multiplying the quantization index coefficient by 100 to obtain a standardized grading value.
The standardized scoring values corresponding to the evaluation factors are given corresponding values according to the influence degree of the standardized scoring values on the quantification of the work of the fowls science and technology attendant. The evaluation standards of each evaluation factor are determined by the file surveys of the province science and technology parlor management departments and related experts.
Further, in step S101, the forward factor quantization method expression is:
wherein y is i A quantization index coefficient for the evaluation factor i; y is Y i A measurement value of the evaluation factor i; y is Y min Measuring a lower limit value for the evaluation factor i; y is Y max Upper limit measurement value for the evaluation factor i;
the expression of the negative evaluation factor quantification method is as follows:
wherein y is i A quantization index coefficient for the evaluation factor i; y is Y i A measurement value of the evaluation factor i; y is Y min Measuring a lower limit value for the evaluation factor i; y is Y max The upper limit measurement value of the evaluation factor i.
In the process of quantifying and evaluating the works of the scientific and technological panelists, each evaluation factor is normalized and scored through a positive factor quantification method and a negative evaluation factor quantification method. Basic indexes forming the work quantification of the science and technology attendant all have own dimension and magnitude, and the dimensions of the indexes are different from each other, so that the indexes cannot be directly compared and calculated. All the evaluation factors can be directly calculated by normalizing the evaluation values.
Further, in step S2, determining the weight coefficient of the evaluation factor by the analytic hierarchy process includes the following steps:
s201, comparing the importance of n evaluation factors in pairs by adopting a 1-9 scale method to obtain a quantification result, and if the comparison value of the evaluation factor i relative to the evaluation factor j is b ij The comparison value of the evaluation factor j to the evaluation factor i is 1/b ij Establishing a judgment matrix B of n-order, wherein the expression is as follows:
s202, calculating a maximum characteristic root max lambda of the matrix B, and calculating a matrix consistency index CI:
if the CI value is smaller, the consistency of the matrix B is better, the consistency of the matrix B is checked by the matrix consistency ratio CR, and when CR is smaller than 0.1, the consistency of the matrix B is acceptable, step S203 is performed, where the expression of CR is:
wherein RI is a random consistency index.
S203, calculating a feature vector P= [ P ] corresponding to the maximum feature root max lambda 1 P 2 …P n ] T And carrying out normalization processing on the P to obtain a weight coefficient w of the evaluation factor.
The invention is divided into five major categories based on the qualified lines by evaluating, namely comprehensive categories, excellent propaganda science and technology specially-assigned persons, excellent science and technology knowledge propaganda persons, excellent science and technology innovation entrepreneurs and excellent rural barren and rich lead persons.
In the present invention, the evaluation factors under the policy propaganda latitude have no data, so that the evaluation factors under the policy propaganda latitude are analyzed by a hierarchical analysis method, and the calculation results are shown in table 2. The CI value is calculated to be 0.038 according to the 4-order judgment matrix, and the CR value is calculated to be 0.030<0.1, which means that the judgment matrix in the research meets consistency test, and the calculated weights have consistency.
TABLE 2 weight of index for superior propaganda technology Telecommunications
From the weight coefficient of the calculation result, the scientific and technological specialization staff obtains the national propaganda with the maximum weight of 0.3, secondly, the satisfaction degree of the management object is 0.17, which is 0.18 in the provincial level.
Further, in step S2, determining the weight coefficient of the evaluation factor by the entropy weight method includes the following steps:
s211, establishing an evaluation factor subdomain U= { U 1 ,u 2 ,…,u m Establishing an evaluation level domain v= { V }, which includes m evaluation factors 1 ,v 2 ,…,v n Establishing a fuzzy relation matrix X through U and V, wherein the expression is as follows:
wherein x is ij The value of the corresponding j-th evaluation factor in the i-th evaluation factors; when a certain evaluation factor x ij The larger the middle j is, the more important the evaluation factor is;
s212, calculating x ij The proportion of the evaluation level j corresponding to the i-th evaluation factor in the total number n of the evaluation levels is as follows:
s213, calculating the information entropy value e of the j-th evaluation level j The calculation formula is as follows:
wherein, K is a constant,
y ij the quantized index coefficient of the evaluation factor corresponding to the j-th evaluation level;
information entropy e of evaluation factor j j The difference between the value and 1 determines the information utility value coefficient of the evaluation factor, and the information utility value coefficient is weightedThe magnitude of the weight directly affects, the smaller the value of the information utility value is, the lower the importance of the corresponding evaluation factor is, and the lower the weight coefficient of the evaluation factor is, wherein the information utility value coefficient d of the evaluation factor j is j The expression of (2) is:
d j ＝1-e j
s214, evaluating the information utility value coefficient d of the grade j j Calculating the weight coefficient of the evaluation level j, wherein the expression is as follows:
wherein w is j And (5) the weight coefficient corresponding to the j-th evaluation level.
The invention calculates the weight coefficient of the evaluation factors under three latitudes of science and technology propagation, innovation and creation and head-brought enrichment.
In the calculation of the superior technology knowledge propagator, the weights of 11 superior technology knowledge propagators such as basic service under the technology propagation latitude are calculated by using the entropy method, and the obtained results are shown in table 3. The first five rights are respectively the number of popularization technologies (0.305), the number of online services (0.155), the number of service subjects (0.139), the technological training (0.13) and the basic service (0.099).
TABLE 3 index weight for superior technology knowledge propagators
The weights of 7 innovation entrepreneurs such as the formation (other) benefit community numbers under the innovation entrepreneur latitude are calculated by using an entropy method, and the obtained results are shown in table 4. The number of enterprises (0.348) and the project standing condition (0.313) account for the main weight of the innovation and the creation.
Table 4 Innovative weights in the index weight
The weight coefficient of 3 belt head enrichment such as the number of directly served farmers under the latitude of the belt head enrichment is calculated by using an entropy method, and the obtained result is shown in table 5.
Table 5 leading enrichment indicator weight
The weight of each of the superior propaganda science and technology super-derivative, the superior science and technology knowledge propaganda person, the science and technology innovation entrepreneur who is lean and rich in village is 25%, and various weights after refinement are shown in table 6.
Table 6 comprehensive quantitative assessment index weight for scientific and technological specialization staff
The invention adopts a comprehensive index system method to establish a quantitative evaluation system for the work of the scientific and technological specialities. The index system method needs to classify and combine a plurality of indexes such as work performance, social evaluation and the like which are objectively connected, and further scientifically and reasonably establishes a set of evaluation index system. The method can screen, extract and integrate massive and complex information, fully considers the diversity and complexity of the service work of the science and technology attendant, and integrates different types of evaluation factors and information, thereby comprehensively and comprehensively reflecting the work effect of the science and technology attendant.
Further, the expression of the scientific and technological attendant work quantitative evaluation model is as follows:
s is the total score of the work quantification of the science and technology attendant, namely the annual work performance total score of the science and technology attendant; w (w) i The weight coefficient is the evaluation factor; s is S i A normalized score value representing an evaluation factor; n is the number of evaluation factors.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash memory (flashRAM). Memory is an example of a computer-readable medium.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.
Claims (7)
1. The scientific and technological attendant work quantitative evaluation method based on the cloud platform is characterized by comprising the following steps of:
s1, constructing an evaluation index system of a science and technology attendant, and carrying out standardized scoring on evaluation factors in the evaluation index system based on data of a cloud platform to obtain standardized scoring values of the evaluation factors;
and S2, determining the weight coefficient of the evaluation factor through an analytic hierarchy process and an entropy weight process, and establishing a scientific and technological specialization staff work quantitative evaluation model.
2. The quantitative evaluation method for the technological specialization staff based on the cloud platform according to claim 1 is characterized in that in the step S1, the evaluation latitudes are determined according to requirements, primary indexes are arranged under each evaluation latitude, secondary indexes are arranged under part of the primary indexes, and the construction of an evaluation index system is completed;
the evaluation factor includes a primary index and a secondary index.
3. The quantitative evaluation method for the technological specialization staff based on the cloud platform according to claim 1, wherein in the step S1, the data based on the cloud platform performs standardized scoring on the evaluation factors in the evaluation index system, and obtaining the standardized scoring value of the evaluation factors includes:
s101, carrying out quantization treatment on the evaluation factors by a positive factor quantization method and a negative factor quantization method to obtain quantization index coefficients;
s102, multiplying the quantization index coefficient by 100 to obtain a standardized grading value.
4. The cloud platform-based scientific and technological attendant work quantitative evaluation method according to claim 3, wherein in the step S101, the forward factor quantitative method expression is:
wherein y is i A quantization index coefficient for the evaluation factor i; y is Y i A measurement value of the evaluation factor i; y is Y min Measuring a lower limit value for the evaluation factor i; y is Y max Upper limit measurement value for the evaluation factor i;
the negative evaluation factor quantification method expression is as follows:
wherein y is i A quantization index coefficient for the evaluation factor i; y is Y i A measurement value of the evaluation factor i; y is Y min Measuring a lower limit value for the evaluation factor i; y is Y max The upper limit measurement value of the evaluation factor i.
5. The quantitative evaluation method for the technical and scientific attendant works based on the cloud platform as claimed in claim 4, wherein in the step S2, the determination of the weight coefficient of the evaluation factor by the analytic hierarchy process comprises the following steps:
s201, comparing the importance of n evaluation factors in pairs by adopting a 1-9 scale method to obtain a quantification result, and if the evaluation is performedThe comparison value of the factor i relative to the evaluation factor j is b ij The comparison value of the evaluation factor j to the evaluation factor i is 1/b ij Establishing a judgment matrix B of n-order, wherein the expression is as follows:
s202, calculating a maximum characteristic root max lambda of the matrix B, and calculating a matrix consistency index CI:
if the CI value is smaller, the consistency of the matrix B is better, the consistency of the matrix B is checked by the matrix consistency ratio CR, and when CR is smaller than 0.1, the consistency of the matrix B is acceptable, step S203 is performed, where the expression of CR is:
wherein RI is a random consistency index.
S203, calculating a feature vector P= [ P ] corresponding to the maximum feature root max lambda 1 P 2 …P n ] T And carrying out normalization processing on the P to obtain a weight coefficient w of the evaluation factor.
6. The quantitative evaluation method for the technical and scientific attendant works based on the cloud platform according to claim 5, wherein in the step S2, the determination of the weight coefficient of the evaluation factor by the entropy weight method comprises the following steps:
s211, establishing an evaluation factor subdomain U= { U 1 ,u 2 ,…,u m Establishing an evaluation level domain v= { V }, which includes m evaluation factors 1 ,v 2 ,…,v n Establishing a fuzzy relation matrix X through U and V, wherein the expression is as follows:
wherein x is ij The value of the corresponding j-th evaluation factor in the i-th evaluation factors; when a certain evaluation factor x ij The larger the middle j is, the more important the evaluation factor is;
s212, calculating x ij The proportion of the evaluation level j corresponding to the i-th evaluation factor in the total number n of the evaluation levels is as follows:
s213, calculating the information entropy value e of the j-th evaluation level j The calculation formula is as follows:
wherein, K is a constant,
y ij the quantized index coefficient of the evaluation factor corresponding to the j-th evaluation level;
information entropy e of evaluation factor j j The difference between the value of the information utility coefficient and 1 determines the value of the information utility coefficient of the evaluation factor, and the value of the information utility coefficient directly affects the weight, wherein the smaller the value of the information utility value is, the lower the importance of the corresponding evaluation factor is, the lower the weight coefficient of the evaluation factor is, and the information utility value coefficient d of the evaluation factor j is j The expression of (2) is:
d j ＝1-e j
s214, evaluating the information utility value coefficient d of the grade j j Calculating the weight coefficient of the evaluation level j, wherein the expression is as follows:
wherein w is j And (5) the weight coefficient corresponding to the j-th evaluation level.
7. The cloud platform-based quantitative evaluation method for the scientific and technological panelist work of claim 6, wherein the quantitative evaluation model expression of the scientific and technological panelist work is:
s is the total score of the work quantification of the science and technology attendant, namely the annual work performance total score of the science and technology attendant; w (w) i The weight coefficient is the evaluation factor; s is S i A normalized score value representing an evaluation factor; n is the number of evaluation factors.
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