CN114048977A - Engineer classification method and device and terminal equipment - Google Patents

Engineer classification method and device and terminal equipment Download PDF

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CN114048977A
CN114048977A CN202111265866.1A CN202111265866A CN114048977A CN 114048977 A CN114048977 A CN 114048977A CN 202111265866 A CN202111265866 A CN 202111265866A CN 114048977 A CN114048977 A CN 114048977A
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engineer
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王国伟
朱红坤
贺光华
李奇隆
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Chongqing Chuannan Environmental Protection Technology Co ltd
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Abstract

The invention is suitable for the technical field of computers, and provides an engineer classification method, an engineer classification device and terminal equipment, wherein the method comprises the following steps: constructing an alternative engineer tag library, and screening out engineer grading indexes from the alternative engineer tag library; constructing a hierarchical structure of the engineer grading indexes by using a hierarchical analysis method, and calculating the hierarchical single sequence and the hierarchical total sequence of each engineer grading index; acquiring the index weight of each index relative to the classification problem of the engineer according to the hierarchy single sequencing result and the hierarchy total sequencing result; and analyzing the target engineer by using the engineer grading problem, and grading the target engineer according to the analysis result and the index weight. The invention can solve the quantization problem in the hierarchical evaluation process of engineers.

Description

Engineer classification method and device and terminal equipment
Technical Field
The invention relates to the technical field of computers, in particular to an engineer classification method, an engineer classification device and terminal equipment.
Background
Under the background of big data and the internet of things, an online household appliance maintenance platform is developed vigorously, and mainly comprises a PC webpage end, a mobile end applet, a mobile end APP and the like, and the online household appliance maintenance platform can receive orders in real time and provide home maintenance service, and tracks the states of the orders in real time in a visual mode to form an online household appliance maintenance internet of things. Through the online household appliance maintenance platform, massive order information can be analyzed and processed in time, corresponding processing result auxiliary decision suggestions are made, and the whole order receiving, management and service process of the online household appliance maintenance system is managed in a more detailed and dynamic mode, so that reliable maintenance service is provided for users.
The arrangement and dispatch of maintenance engineers are important links from online service to offline service, and skills and service levels influence willingness of customers to select maintenance company service and impression of company service, so that a hierarchy of the maintenance engineers needs to be established, on one hand, the working enthusiasm of the engineers can be fully mobilized, and on the other hand, the engineers are arranged in a targeted manner according to different customer groups and different service requirements when maintenance service scheduling is carried out.
However, at present, an engineer classification method is generally used to score factors in each evaluation object factor set, and when the number of evaluation people is too large, the workload is huge, and human resources cannot meet the requirements, so that the scheme cannot be practically implemented.
Disclosure of Invention
The invention mainly aims to provide a method for solving the problems that in the prior art, an engineer classification method is huge in workload, and human resources cannot meet requirements, so that the method cannot be implemented.
In order to achieve the above object, a first aspect of an embodiment of the present invention provides an engineer classification method, including:
constructing an alternative engineer tag library, and screening out engineer grading indexes from the alternative engineer tag library;
constructing a hierarchical structure of the engineer grading indexes by using a hierarchical analysis method, and calculating the hierarchical single sequence and the hierarchical total sequence of each engineer grading index;
acquiring the index weight of each index relative to the classification problem of the engineer according to the hierarchy single sequencing result and the hierarchy total sequencing result;
and analyzing the target engineer by using an engineer grading problem, and grading the target engineer according to an analysis result and the index weight.
With reference to the first aspect of the embodiment of the present invention, in the first embodiment of the present invention, constructing an alternative tag index library includes:
acquiring original data related to maintenance service and a pre-constructed engineer label;
and perfecting the content of the engineer label according to the original data to generate a candidate engineer label library.
With reference to the first implementation manner of the first aspect of the embodiment of the present invention, in the second implementation manner of the present invention, the engineer tag includes a static tag and a dynamic tag;
screening out engineer grading indexes from the alternative engineer label library, wherein the engineer grading indexes comprise:
and screening the classification indexes of the engineers in the alternative engineer label library by a Delphi method based on the dynamic labels.
With reference to the first aspect of the embodiment of the present invention, in the third embodiment of the present invention, the building a hierarchical structure of the engineer classification indexes by using a hierarchical analysis method, and calculating a hierarchical single rank and a hierarchical total rank of each engineer classification index includes:
constructing a hierarchical structure of the engineer classification indexes according to the subordination relation of the engineer classification indexes, wherein the hierarchical structure comprises a first layer to an Nth layer, the engineer classification indexes of the Nth layer are divided into a plurality of groups, and the engineer classification indexes belong to an (N-1) th layer;
constructing a judgment matrix based on the engineer classification index of the nth layer;
calculating the hierarchical single sequence of the engineer hierarchical index of the nth layer according to the judgment matrix, and calculating the total hierarchical sequence according to the hierarchical single sequence;
wherein N is a positive integer, and N is a positive integer greater than 2 and less than or equal to N.
With reference to the first aspect of the embodiments of the present invention, in the fourth embodiment of the present invention, after the hierarchical structure of the engineer classification indexes is constructed by using the analytic hierarchy process, before the hierarchical order and the total hierarchical order of each engineer classification index are calculated, the method includes:
carrying out consistency check on the judgment matrix by using a numerical table of consistency indexes, consistency ratios and random consistency indexes;
after the hierarchical single ordering and the hierarchical total ordering of each engineer hierarchical index are calculated, the method further comprises the following steps:
carrying out consistency check on the total hierarchical ordering by using a numerical table of consistency indexes, consistency ratios and random consistency indexes;
and if the consistency check is passed, calculating the total hierarchical order by using all the hierarchical single-order orders, and taking the total hierarchical order as a final weight result.
With reference to the third aspect of the first aspect of the embodiments of the present invention, in a fourth embodiment of the present invention, if the consistency check fails, the judgment matrix is optimized by using a particle swarm optimization.
With reference to the first aspect of the embodiments of the present invention, in a fifth embodiment of the present invention, before analyzing a target engineer using an engineer classification problem, the method includes:
and counting data in the engineer grading indexes, and dividing the data of each engineer grading index into K intervals, wherein the K intervals are represented by K label values, and K is a positive integer.
A second aspect of an embodiment of the present invention provides an engineer classification apparatus, including:
the system comprises an engineer grading index acquisition module, a classification index analysis module and a classification index analysis module, wherein the engineer grading index acquisition module is used for constructing a candidate engineer tag library and screening out engineer grading indexes from the candidate engineer tag library;
the engineer grading index sorting module is used for constructing a hierarchical structure of the engineer grading indexes through a hierarchical analysis method and calculating the hierarchical single sorting and the hierarchical total sorting of the engineer grading indexes;
the index weight calculation block is used for obtaining the index weight of each index relative to the classification problem of the engineer according to the hierarchy single-sequencing result and the hierarchy total-sequencing result;
and the engineer grading module is used for analyzing the target engineer by using the engineer grading problem and grading the target engineer according to the analysis result and the index weight.
A third aspect of embodiments of the present invention provides a terminal device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the steps of the method provided in the first aspect when executing the computer program.
A fourth aspect of embodiments of the present invention provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the method as provided in the first aspect above.
The embodiment of the invention provides an engineer classification method, which can directly analyze a target engineer through an engineer classification problem and index weight, thereby realizing the classification of the engineer without manually classifying factors in each evaluation object factor set, and avoiding the problem that the traditional classification method cannot be implemented when the number of the engineers to be classified is too large.
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Fig. 1 is a schematic flow chart illustrating an implementation of an engineer classification method according to an embodiment of the present invention;
FIG. 2 is a detailed flowchart illustrating the step S102 in FIG. 1;
fig. 3 is a schematic structural diagram of an engineer classification apparatus according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that, in this document, 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 an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Suffixes such as "module", "part", or "unit" used to denote elements are used herein only for the convenience of description of the present invention, and have no specific meaning in themselves. Thus, "module" and "component" may be used in a mixture.
The embodiment of the invention provides an engineer classification method, which can directly analyze a target engineer through an engineer classification problem and index weight, thereby realizing the classification of the engineer without manually classifying factors in each evaluation object factor set, and avoiding the problem that the traditional classification method cannot be implemented when the number of the engineers to be classified is too large, and based on the problem, as shown in fig. 1, the engineer classification method disclosed by the embodiment of the invention comprises the following steps:
s101, constructing a candidate engineer tag library, and screening out engineer grading indexes from the candidate engineer tag library.
In the step S101, the candidate engineer tag library includes various engineer tags extracted from the service records of the engineers, and can be divided into two categories, namely, engineer personal information and engineer service quality information, so as to avoid the problem that the selected evaluation standard is subjective and not reasonable enough due to obtaining of the engineer tags through consultation and summarization.
In an embodiment, in the step S101, one implementation manner of building the candidate engineer tag library may be:
acquiring original data related to maintenance service and a pre-constructed engineer label;
and perfecting the content of the engineer label according to the original data to generate a candidate engineer label library.
The original data related to the maintenance service comprises original data such as data related to the maintenance service, engineer behavior data and engineer personal information acquired from a local service database or a partner platform; therefore, in the embodiment of the invention, the process of constructing the alternative engineer tag library utilizes the portrait technology to extract the tag library capable of reflecting the service quality and the service level of the maintenance engineer from the service data, thereby realizing the full utilization of the service data.
Wherein the engineer tags include static tags and dynamic tags;
in step S101, one implementation manner of screening out the engineer classification index from the candidate engineer tag library may be:
and screening the classification indexes of the engineers in the alternative engineer label library by a Delphi method based on the dynamic labels.
It should be noted that the delofield method mainly collects the opinions of experts, so as to screen the grading indexes of engineers, and the implementation process thereof may be as follows:
step 1: forming an expert group, wherein the number of people is more than 10, and the expert group is required to be sufficiently familiar with the engineering business;
step 2: making a questionnaire, wherein the questionnaire mainly comprises a question background, a questionnaire filling mode, a label to be screened, whether the expert fills in the label properly or not, properly fills in 1 and improperly fills in 0, and the expert fills in an index which the expert thinks can be used as grading;
and step 3: the experts fill in the questionnaire, independently fill in the questionnaire, fill in the questionnaire anonymously, and recycle the questionnaire after all the experts fill in;
and 4, step 4: gathering expert opinions, counting the recovered questionnaires, filling proper labels in 70% or more of the experts to be used as indexes for classification of engineers, screening the rest, and adding the indexes added by the experts into labels to be screened;
and 5: and (5) judging whether the expert opinions are consistent, if so, obtaining the final grading evaluation index, and if not, returning to the step 2.
S102, constructing a hierarchical structure of the engineer grading indexes through a hierarchical analysis method, and calculating the hierarchical single sequence and the hierarchical total sequence of each engineer grading index.
In the step S102, the hierarchy of the engineer classification index is mainly the subordinate hierarchy, for example, in the engineer classification index ABCD, the engineer classification index BCD determines the engineer classification index a, in the hierarchy, the engineer classification index BCD belongs to the engineer classification index a, and in the engineer classification index BCD, the hierarchy is sorted. In the engineer ranking index A1B1C1D1, the engineer ranking index B1C1D1 determines the engineer ranking index A1, in the hierarchical structure, the engineer ranking index B1C1D1 belongs to the engineer ranking index A1, and in the engineer ranking index B1C1D1, a hierarchical single sort is to be performed. And the total ranking of the levels is performed on the engineer grading index A, the engineer grading index A1, the engineer grading index BCD and the engineer grading index B1C1D 1.
And S103, acquiring the index weight of each index relative to the classification problem of the engineer according to the hierarchy single-order result and the hierarchy total-order result.
And S104, analyzing the target engineer by using the engineer grading problem, and grading the target engineer according to an analysis result and the index weight.
In the step S104, the target engineer is analyzed using the engineer classification problem, that is, the original data related to the maintenance service based on the target engineer is scored under the engineer classification index obtained in the step, and the target engineer is classified according to the analysis result and the index weight, that is, the final scoring result.
The engineer rating problem corresponds to an engineer rating index, for example, the engineer rating problem is how profitable the target engineer is, and the engineer rating index includes a total completed order amount, a monthly total profit of service production, and a monthly total profit of service production.
Therefore, before analyzing the target engineer using the engineer classification problem, a scoring interval of each engineer classification index is further set, which includes:
and counting data in the engineer grading indexes, and dividing the data of each engineer grading index into K intervals, wherein the K intervals are represented by K label values, and K is a positive integer.
For example, the engineer classification index B is divided into 5 sections from small to large, a label value is set for each eigenvalue falling in a different section, and the label value is { excellent, good, medium, poor }, and the corresponding score values are 100, 80, 60, 40, and 20.
It is assumed that in the hierarchical single-rank result, i.e., the engineer ranking index B is in the engineer ranking index BCD, the rank is first, the weight is 3, and the remaining weights are 2 and 1. In the overall hierarchical ranking result, first, the engineer ranking index A is first, the weight is set to 2, the engineer ranking index A1 is second, the weight is set to 1, and then the actual weight of the engineer ranking index B is
Figure BDA0003326909500000081
Therefore, if the label value of the engineer ranking index B is excellent, when the target engineer is ranked according to the analysis result and the index weight, the calculation based on the engineer ranking index B should be:
Figure BDA0003326909500000082
as shown in fig. 2, the embodiment of the present invention further illustrates an implementation manner of the step S102, which calculates the hierarchical single rank and the hierarchical total rank of the engineer classification index through the judgment matrix, including but not limited to the following steps:
s1021, constructing a hierarchical structure of the engineer classification indexes according to the subordination relation of the engineer classification indexes, wherein the hierarchical structure comprises a first layer to an Nth layer, the engineer classification indexes of the Nth layer are divided into a plurality of groups, and the engineer classification indexes belong to an (N-1) th layer;
s1022, constructing a judgment matrix based on the nth-layer engineer grading index;
s1023, calculating the hierarchical single sequence of the engineer hierarchical index of the nth layer according to the judgment matrix, and calculating the total hierarchical sequence according to the hierarchical single sequence;
wherein N is a positive integer, and N is a positive integer greater than 2 and less than or equal to N.
In a specific application, the numerical values in the determination matrix are filled in by experts according to the delphi method, and therefore, when the determination matrix is used, the determination matrix may be inconsistent, so that the problem that the index weight calculated in the following step S103 is inaccurate is solved, and therefore, in the embodiment of the present invention, after the hierarchical structure of the engineer classification index is constructed by the analytic hierarchy method, before the hierarchical single ranking and the hierarchical total ranking of each engineer classification index are calculated, the method further includes:
carrying out consistency check on the judgment matrix by using a numerical table of consistency indexes, consistency ratios and random consistency indexes;
if the consistency check is passed, calculating the total hierarchical ranking by using all the hierarchical single-ranking and taking the total hierarchical ranking as a final weight result;
after the hierarchical single ordering and the hierarchical total ordering of each engineer hierarchical index are calculated, the method further comprises the following steps:
and carrying out consistency check on the total hierarchical ordering by using a numerical table of consistency indexes, consistency ratios and random consistency indexes.
And if the consistency check fails, optimizing the judgment matrix by utilizing a particle swarm algorithm.
In the embodiment of the invention, the accuracy of the final grading result of the engineer is directly influenced by the grading index of the engineer and the judgment matrix, the quantitative processing of the grading index of the engineer is realized by combining the Delphi method and the analytic hierarchy process, the influence caused by authority when the index is weighted is eliminated by the anonymity of the Delphi method, and the feedback of multiple rounds of information of the Delphi method ensures that the basic idea and the knowledge of the information of the expert can be basically reflected by the screening result and the comparison result of the importance of the grading index of the maintenance engineer finally, so the calculation result of the finally selected grading index of the engineer and the index weight is objective, reasonable and reliable. And the application of the analytic hierarchy process allows a maintenance engineer to be regarded as a system in a grading manner, and makes a decision according to a decomposition, comparison, judgment and comprehensive thinking mode, so that the effectiveness, reasonability and scientificity of the decision are improved.
The present embodiment further describes the use and optimization of the determination matrix in step S102 by using actual engineer classification indexes.
Firstly, assuming that the total order amount completed by the engineer grading index, the monthly order amount completed, the total service production profit, the monthly service production profit, the service success rate, the average order improvement times, the engineer technical grade, the repair rate, the on-time door rate, the five-star goodness rate, the one-star poor rate, the complaint rate, the re-election rate, the work benefit, the skill level and the service quality, the hierarchy of the engineer grading index constructed according to the subordinate relationship is as shown in the following table 1:
Figure BDA0003326909500000091
Figure BDA0003326909500000101
TABLE 1
Then, for the engineer classification index of each layer, constructing a judgment matrix, wherein the judgment matrix constructed based on the layer B is a criterion layer judgment matrix which is shown in table 2; the judgment matrix constructed based on the layer C is a work benefit judgment matrix, a skill level judgment matrix, and a service quality judgment matrix, which are shown in tables 3, 4, and 5:
three dimensions Efficiency of work Skill level Quality of service
Efficiency of work 1
Skill level 1
Quality of service 1
TABLE 2
Figure BDA0003326909500000102
TABLE 3
Figure BDA0003326909500000103
TABLE 4
Four indexes Punctual door rate Five-star goodness of appraisal One-star difference rating Complaint rate of
Punctual door rate 1
Five-star goodness of appraisal 1
One-star difference rating 1
Complaint rate of 1
TABLE 5
The values in the above judgment matrix are filled in by experts, but in the embodiment of the present invention, the values are still performed according to the delphire method, which includes:
1) making a judgment matrix questionnaire, and enabling experts to independently fill in the whole filling process according to the scale method shown in table 6 in the blank area filling scales in tables 2, 3, 4 and 5, wherein the experts are anonymous and do not generate discussion and communication;
Figure BDA0003326909500000111
TABLE 6
2) Gathering expert opinions, and giving scores a given by experts according to the following formula (1)iCarrying out weighted average calculation on the number m of the persons participating in the expert, wherein E is an expert opinion statistical result;
Figure BDA0003326909500000112
the expert opinion dispersion σ is calculated as a standard deviation according to equation (2).
Figure BDA0003326909500000113
Setting sigma0When the ith correlation is calculatediSatisfy sigmai＜σ0End when not otherwiseReturn to a not satisfiediThe importance was re-evaluated.
Through the steps, values of engineer grading index total order completion amount, monthly order completion amount, total service production profit, monthly service production profit, service success rate, average order repayment times, engineer technical grade, repair rate, on-time door rate, five-star goodness rate, one-star poor rate, complaint rate and reselected rate in the layer C are calculated, and sequencing of the engineer grading index total order completion amount, monthly order completion amount, total service production profit, monthly service production profit margin, service success rate, average order improvement times, engineer technical grade, repair rate, on-time door rate, five-star goodness rate, one-star poor rate, complaint rate and reselected rate is determined, so that sequencing of the engineer grading index total order completion amount, the monthly order completion amount, the service quality and the like in the layer C is determined and used as hierarchical order sequencing. And calculating values of the work benefit, the skill level and the service quality in the layer B so as to determine the sequence of the engineering in the engineer layering, and combining the values of the layer B and the layer C to obtain the hierarchical total order completion amount of the engineer grading indexes in the layer C, the monthly completion order quantity, the total service production profit, the monthly service production profit, the service success rate, the average order dispatching completion times, the engineering grade, the repair rate, the on-time door rate, the five-star goodness rating, the one-star poor rating, the complaint rate and the reselected rate.
Then, according to the above steps, the embodiment of the present invention further uses the numerical table of the consistency index, the consistency ratio and the random consistency index to check the consistency of the judgment matrix and the total hierarchical ranking, and the essence is to determine the inconsistent allowable range for the judgment matrix, and check the judgment matrix by using the numerical table of the consistency index, the consistency ratio CR < 0.1 and the random consistency index. The identity index is defined as shown in the following formula (3):
Figure BDA0003326909500000121
wherein lambda is the maximum characteristic root of the matrix; n is the matrix order. When CI is 0, judging that the matrix has complete consistency; when the CI is close to 0, judging that the matrix has satisfactory consistency; the larger the CI, the more severe the inconsistency. To measure the magnitude of CI, a random consistency index RI was introduced. The results of the consistency index RI are shown in Table 7:
n 1 2 3 4 5 6 7 8 9 10 11
RI 0 0 0.58 0.90 1.12 1.24 1.32 1.41 1.45 1.49 1.51
table 7 defines the consistency ratio as shown in equation (4):
Figure BDA0003326909500000122
when the consistency ratio CR is less than 0.1, the inconsistency degree of the judgment matrix A is considered to be within the allowable range, and the consistency is satisfied, and the normalized feature vector is used as the weight vector when passing the consistency test.
In the consistency test of the total hierarchical ordering, a layer C is set1，C2，C3,. for factor B in the upper layer (layer B)jThe index of consistency of the hierarchical single-rank order of (j ═ 1, 2., m) is CIjThe random consistency index is RIjThen the consistency ratio of the total ordering is as shown in equation (5):
Figure BDA0003326909500000131
if the consistency ratio CR is less than 0.1, the total hierarchical ranking is calculated by using the single hierarchical ranking through the consistency test and is used as the final weight result.
And finally, if the consistency check fails, solving the problem of matrix inconsistency by using a particle swarm algorithm.
In one embodiment, the following method may also be used to determine whether the matrices are consistent, which is implemented as:
optimizing the optimal value of the target weight by an inertial weight particle swarm algorithm, and judging the importance ratio a of every two indexes in the matrix according to the definition of the judgment matrixij＝ωi/ωjI.e. aijωj＝ωiIf the matrix is judged to have complete consistency, then
Figure BDA0003326909500000132
In the formula, aijIs the relative importance scale of the ith element relative to the jth element; omegaiIs the ith element weight; n is the number of elements, and it can be seen that the smaller the left side of the formula (6), the higher the consistency of the judgment matrix, the more the problem of checking the ranking weight and consistency of the judgment matrix in the analytic hierarchy process can be converted into a nonlinear optimization problem aiming at a specific target and decision:
Figure BDA0003326909500000133
s.t ωi＞0 i＝1，2，3，…，n
Figure BDA0003326909500000134
where cif (n) is a consistency index function, and when cif (n) is 0, a global minimum value is obtained.
In addition, the embodiment of the present invention further shows a specific process for optimizing the judgment matrix by using a particle swarm algorithm, which is as follows:
step 1: initializing the speed and position of each particle in a population, setting the initial position as an original weight of a target to be optimized, setting a search space to be n-dimensional, namely the dimension of each judgment matrix, setting the optimal position Pbest searched by each particle at present as the initial position, and taking the optimal position searched by the particles globally as Gbest;
step 2: an objective function value, i.e., fitness, is calculated for each particle, the objective function being equation (6). The optimal position and fitness value for each particle are stored. If the fitness value of a certain particle is the best in the population, selecting the particle as the position of the population;
step 3: and (5) combining the updated formulas (7) and (8) of the algorithm to adjust the speed and the position of the particles.
Figure BDA0003326909500000141
Figure BDA0003326909500000142
Figure BDA0003326909500000143
In the formula, the inertia coefficient is omegaidIndicating that each particle has its own inertial weight coefficient; α is a coefficient of linear variation, vidScalar magnitude for velocity; Δ h is the function value variation of the particle from one moment to another moment;
step 4: after each position update, the objective function value, i.e. fitness value, of each particle is calculated, and then the best position P found in the history of the particle is foundbestCalculating the corresponding fitness value, comparing the fitness values of the particles with the fitness values, and comparing the fitness values of the particles with the fitness values of the particles if a solution is available, the solution can be compared with the optimal position PbestPreferably, the current position of the particle is regarded as Pbest；
Step 5: comparing the fitness value of each particle with the optimal positions G of all particlesbestCorresponding fitness value, G if one of the particles performs betterbestWill be updated;
step 6: check particle search termination criteria (one for maximum number of iterations: G)max(ii) a The other is the deviation between two adjacent generations within the specified range), and once the assumed conditions are found to be not met, return to Step3 to continue updating the velocity and position of the particle. After the termination, the global optimal position is found to be used as the optimal value of the optimized target weight.
As shown in fig. 3, the embodiment of the present invention further shows an engineer classification apparatus 30, which includes:
the engineer classification index acquisition module 31 is configured to construct an alternative engineer tag library, and screen out an engineer classification index from the alternative engineer tag library;
the engineer grading index sorting module 32 is used for constructing a hierarchy structure of the engineer grading indexes by a analytic hierarchy process and calculating the hierarchical single sorting and the hierarchical total sorting of each engineer grading index;
the index weight calculation block 33 is used for obtaining the index weight of each index relative to the classification problem of the engineer according to the hierarchy single-ranking result and the hierarchy total-ranking result;
and the engineer grading module 34 is configured to analyze the target engineer using an engineer grading problem, and grade the target engineer according to an analysis result and the index weight.
The embodiment of the present invention further provides a terminal device, which includes a memory, a processor, and a computer program stored in the memory and capable of running on the processor, and when the processor executes the computer program, the steps in the engineer classification method described in the foregoing embodiment are implemented.
An embodiment of the present invention further provides a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium, and when the computer program is executed by a processor, the computer program implements the steps in the engineer classification method as described in the foregoing embodiment.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the foregoing embodiments illustrate the present invention in detail, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.

Claims (10)

1. An engineer grading method, comprising:
constructing an alternative engineer tag library, and screening out engineer grading indexes from the alternative engineer tag library;
constructing a hierarchical structure of the engineer grading indexes by using a hierarchical analysis method, and calculating the hierarchical single sequence and the hierarchical total sequence of each engineer grading index;
acquiring the index weight of each index relative to the classification problem of the engineer according to the hierarchy single sequencing result and the hierarchy total sequencing result;
and analyzing the target engineer by using an engineer grading problem, and grading the target engineer according to an analysis result and the index weight.
2. The engineer grading method of claim 1, wherein building a library of alternative label indicators comprises:
acquiring original data related to maintenance service and a pre-constructed engineer label;
and perfecting the content of the engineer label according to the original data to generate a candidate engineer label library.
3. The engineer grading method according to claim 2, wherein the engineer tags include static tags and dynamic tags;
screening out engineer grading indexes from the alternative engineer label library, wherein the engineer grading indexes comprise:
and screening the classification indexes of the engineers in the alternative engineer label library by a Delphi method based on the dynamic labels.
4. The engineer grading method according to claim 1, wherein the hierarchical structure of the engineer grading index is constructed by a hierarchical analysis method, and the calculation of the hierarchical single rank and the hierarchical total rank of each engineer grading index comprises:
constructing a hierarchical structure of the engineer classification indexes according to the subordination relation of the engineer classification indexes, wherein the hierarchical structure comprises a first layer to an Nth layer, the engineer classification indexes of the Nth layer are divided into a plurality of groups, and the engineer classification indexes belong to an (N-1) th layer;
constructing a judgment matrix based on the engineer classification index of the nth layer;
calculating the hierarchical single sequence of the engineer hierarchical index of the nth layer according to the judgment matrix, and calculating the total hierarchical sequence according to the hierarchical single sequence;
wherein N is a positive integer, and N is a positive integer greater than 2 and less than or equal to N.
5. The engineer grading method according to claim 4, wherein after constructing the hierarchy of the engineer grading index by the analytic hierarchy process, before calculating the hierarchical single rank and the hierarchical total rank of each engineer grading index, the method comprises:
carrying out consistency check on the judgment matrix by using a numerical table of consistency indexes, consistency ratios and random consistency indexes;
after the hierarchical single ordering and the hierarchical total ordering of each engineer hierarchical index are calculated, the method further comprises the following steps:
carrying out consistency check on the total hierarchical ordering by using a numerical table of consistency indexes, consistency ratios and random consistency indexes;
and if the consistency check is passed, calculating the total hierarchical order by using all the hierarchical single-order orders, and taking the total hierarchical order as a final weight result.
6. The engineer grading method of claim 4, wherein if the consistency check fails, the decision matrix is optimized using a particle swarm algorithm.
7. The engineer grading method according to claim 1, wherein before analyzing the target engineer using the engineer grading problem, comprising:
and counting data in the engineer grading indexes, and dividing the data of each engineer grading index into K intervals, wherein the K intervals are represented by K label values, and K is a positive integer.
8. An engineer grading apparatus, comprising:
the system comprises an engineer grading index acquisition module, a classification index analysis module and a classification index analysis module, wherein the engineer grading index acquisition module is used for constructing a candidate engineer tag library and screening out engineer grading indexes from the candidate engineer tag library;
the engineer grading index sorting module is used for constructing a hierarchical structure of the engineer grading indexes through a hierarchical analysis method and calculating the hierarchical single sorting and the hierarchical total sorting of the engineer grading indexes;
the index weight calculation block is used for obtaining the index weight of each index relative to the classification problem of the engineer according to the hierarchy single-sequencing result and the hierarchy total-sequencing result;
and the engineer grading module is used for analyzing the target engineer by using the engineer grading problem and grading the target engineer according to the analysis result and the index weight.
9. A terminal device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the engineer grading method as claimed in any one of claims 1 to 7 when executing the computer program.
10. A storage medium being a computer readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, performs the steps of the engineer grading method as claimed in any one of claims 1 to 7.
CN202111265866.1A 2021-10-28 2021-10-28 Engineer classification method and device and terminal equipment Pending CN114048977A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116740525A (en) * 2023-08-16 2023-09-12 南京迅集科技有限公司 Intelligent manufacturing quality management method based on data fusion

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116740525A (en) * 2023-08-16 2023-09-12 南京迅集科技有限公司 Intelligent manufacturing quality management method based on data fusion
CN116740525B (en) * 2023-08-16 2023-10-31 南京迅集科技有限公司 Intelligent manufacturing quality management method based on data fusion

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