CN111223206A - Device evaluation method, device, terminal and computer readable medium - Google Patents
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Abstract
The application provides a device evaluation method, which comprises the following steps: establishing an evaluation index system of the device, and receiving parameter values of indexes to be evaluated generated in the running process of the device, wherein the evaluation index system comprises a plurality of key components, and each key component comprises a plurality of indexes to be evaluated; inputting the parameter values into a membership function, and outputting a membership numerical value of each index to be evaluated; calculating a first weight of each key component in an evaluation index system, and generating a first matrix from all the first weights; converting the membership degree value into an evaluation value, and converting the evaluation value into a fuzzy matrix by a fuzzy comprehensive evaluation method; and generating a plurality of target evaluation values of the device through the first matrix and the fuzzy matrix, and selecting an evaluation result corresponding to the maximum target evaluation value from the plurality of target evaluation values as a target evaluation result according to the corresponding relation between the target evaluation values and the evaluation result. The evaluation result of the application is simple and clear.
Description
Technical Field
The present application relates to the field of device evaluation technologies, and in particular, to a device evaluation method, a device, a terminal, and a computer-readable medium.
Background
The comprehensive transmission device is the core power transmission of a vehicle, the comprehensive transmission device comprises key components such as an oil supply system and a steering pump motor, each key component comprises a plurality of indexes to be evaluated, and if the indexes to be evaluated of the steering pump motor comprise: the high-pressure valve group turns to high pressure, servo system servo pressure and rotor component oil supplementing pressure. These critical components play a crucial role in the operation of the vehicle, and the state of health of the integrated transmission can affect the operational safety of the vehicle. Therefore, there is a need for a health assessment of the integrated transmission of a vehicle, which is currently scored by experts, subjective and inaccurate.
Disclosure of Invention
An object of the embodiments of the present application is to provide a device evaluation method to solve the problem of inaccurate device evaluation. The specific technical scheme is as follows:
in a first aspect, a device evaluation method is provided, the method comprising:
establishing an evaluation index system of the device, and receiving parameter values of indexes to be evaluated generated in the running process of the device, wherein the evaluation index system comprises a plurality of key components, and each key component comprises a plurality of indexes to be evaluated;
inputting the parameter values into a membership function, and outputting a membership numerical value of each index to be evaluated;
calculating a first weight of each key component in the evaluation index system, and generating a first matrix from all the first weights;
converting the membership numerical value into an evaluation numerical value, and converting the evaluation numerical value into a fuzzy matrix by a fuzzy comprehensive evaluation method;
and selecting an evaluation result corresponding to the maximum target evaluation value from the plurality of target evaluation values as a target evaluation result according to the corresponding relation between the target evaluation values and the evaluation result through the plurality of target evaluation values of the first matrix and the fuzzy matrix generation device.
Optionally, the converting the membership value into an evaluation value includes:
calculating a second weight of each evaluation index in the key part;
and converting the membership grade value and the second weight into the evaluation value through fuzzy change.
Optionally, the calculating a second weight of each evaluation index in the related key component includes:
calculating a first sub-weight of each evaluation index in the key component by an analytic hierarchy process;
calculating a second sub-weight of each evaluation index in the key part by an entropy weight method;
and carrying out weighted summation on the first sub-weight and the second sub-weight to obtain the second weight.
Optionally, the generating the plurality of target values by the first matrix and the fuzzy matrix includes:
and generating a target matrix through the product of the first matrix and the fuzzy matrix, and taking a plurality of elements in the target matrix as the plurality of target numerical values.
Optionally, after converting the membership value into an evaluation value, the method further includes:
and selecting the evaluation result corresponding to the maximum evaluation numerical value from the evaluation numerical values according to the corresponding relation between the evaluation numerical value and the evaluation result in each key component as the analysis result in each key component, wherein the analysis result represents the health state of the key component.
Optionally, the calculating a first weight occupied by each of the key components in the evaluation index system includes:
calculating a third sub-weight of each key component in the evaluation index system by an analytic hierarchy process;
calculating the fourth sub-weight of each evaluation index in the key part by an entropy weight method;
and carrying out weighted summation on the third sub-weight and the fourth sub-weight to obtain the first weight.
In a second aspect, an apparatus evaluation apparatus is provided, wherein the apparatus comprises:
the device comprises an establishing module, a judging module and a judging module, wherein the establishing module is used for establishing an evaluation index system of the device and receiving parameter values of indexes to be evaluated generated in the running process of the device, the evaluation index system comprises a plurality of key components, and each key component comprises a plurality of indexes to be evaluated;
the input and output module is used for inputting the parameter values into a membership function and outputting the membership numerical value of each index to be evaluated;
the calculation module is used for calculating a first weight occupied by each key component in the evaluation index system and generating a first matrix from all the first weights;
the conversion module is used for converting the membership numerical value into an evaluation numerical value and converting the evaluation numerical value into a fuzzy matrix through a fuzzy comprehensive evaluation method;
and the generating module is used for generating a plurality of target evaluation values of the device through the first matrix and the fuzzy matrix, and selecting an evaluation result corresponding to the largest target evaluation value from the plurality of target evaluation values as a target evaluation result according to the corresponding relation between the target evaluation values and the evaluation result.
Optionally, the conversion module includes:
the calculating unit is used for calculating a second weight of each evaluation index in the key component;
and the conversion unit is used for converting the membership degree value and the second weight into the evaluation value through fuzzy change.
In a third aspect, an electronic device is provided, which includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
a processor for implementing any of the method steps described herein when executing the program stored in the memory.
In a fourth aspect, a computer-readable storage medium is provided, in which a computer program is stored which, when being executed by a processor, carries out any of the method steps.
The embodiment of the application has the following beneficial effects:
the embodiment of the application provides a device evaluation method, the method converts the parameter value of the index to be evaluated into a target evaluation value of the device, and selects the evaluation result corresponding to the largest value in the target evaluation values as the target evaluation result according to the corresponding relation between the target evaluation value and the evaluation result, the evaluation result is simple and clear, in addition, the method combines an analytic hierarchy process and an entropy weight process, and the reasonability of the result is ensured.
Of course, not all advantages described above need to be achieved at the same time in the practice of any one product or method of the present application.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a flowchart of a device evaluation method according to an embodiment of the present application;
FIG. 2 is a block diagram of an integrated transmission provided in accordance with an embodiment of the present application;
FIG. 3 is a flow chart of a method for converting to an evaluation value according to an embodiment of the present application;
FIG. 4 is a schematic structural diagram of an apparatus evaluation device according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The embodiment of the application provides a device evaluation method which can be applied to a server used for evaluating the health state of an integrated transmission device.
A device evaluation method provided in the embodiments of the present application will be described in detail below with reference to specific embodiments, as shown in fig. 1, the specific steps are as follows:
step 101: the method comprises the steps of establishing an evaluation index system of the device, and receiving parameter values of indexes to be evaluated generated in the operation process of the device, wherein the evaluation index system comprises a plurality of key components, and each key component comprises a plurality of indexes to be evaluated.
In this embodiment, the device is a device to be evaluated, and the device may include a plurality of key components, where each key component corresponds to a plurality of preset indexes to be evaluated. For example, the device is an integrated transmission device of a vehicle, the integrated transmission device comprises a plurality of key components, such as a front transmission, an oil supply system, a steering pump motor, a hydraulic control system and the like, wherein each key component comprises a plurality of indexes to be evaluated, the front transmission comprises a gear shaft vibration peak value and a bearing vibration kurtosis value, and the steering pump motor comprises a high-pressure valve bank steering high pressure, a servo system servo pressure and a rotor component oil supplementing pressure.
In the embodiment of the application, the server establishes an evaluation index system of the integrated transmission device according to the key components of the integrated transmission device and the index to be evaluated, as shown in fig. 2, wherein the evaluation index system is the key components of the integrated transmission device and the index to be evaluated in sequence from top to bottom. The server receives a parameter value of the index to be evaluated, which is generated by the comprehensive transmission device in the operation process, and the parameter value represents the working state of the index to be evaluated. In the embodiment of the present application, the parameter values of the index to be evaluated are shown in table one:
watch 1
Wherein, Y1To Y8Eight key components of the integrated transmission, D1To D32And representing the index to be evaluated of the comprehensive transmission device.
In order to improve the accuracy of the parameter values of the index to be evaluated, the server receives three groups of parameter values of the index to be evaluated.
Step 102: and inputting the parameter values into a membership function, and outputting a membership numerical value of each index to be evaluated.
In the embodiment of the present application, the health status of the device is first graded. In the embodiment of the application, the health state of the comprehensive transmission device is divided into five grades of health, sub-health, availability, failure and scrappage, corresponding membership functions are established according to the five grades, and the server inputs the received parameter values of the indexes to be evaluated into the membership functions and outputs the membership numerical values of each index to be evaluated. In the embodiment of the application, the trapezoidal distribution membership function is adopted, the calculation time consumption of the function is less, and the real-time performance of the control system is better.
Step 103: and calculating a first weight occupied by each key component in the evaluation index system, and generating a first matrix by using all the first weights.
In the embodiment of the application, after receiving the parameter values of the indexes to be evaluated, the server calculates a first weight occupied by each key component in an evaluation index system, specifically, the server calculates a third sub-weight occupied by each key component in the evaluation index system through an analytic hierarchy process, calculates a fourth sub-weight occupied by each evaluation index in the key component to which the evaluation index belongs through an entropy weight method, then performs weighted summation on the third sub-weight and the fourth sub-weight to obtain the first weight, and finally, the server generates a first matrix from all the obtained first weights. Wherein, the server adopts an analytic hierarchy process and an entropy weight process without the sequence,
for example, after receiving the parameter value of the index to be evaluated as shown in table one, the server calculates the third sub-weight ω of each key component in the evaluation index system by using an analytic hierarchy process*Wherein ω is*In particular to a method for preparing a high-performance nano-silver alloy,
ω*＝[0.0183,0.0247,0.0350,0.0507,0.0739,0.1075,0.1555,0.2223,0.3123]
the server calculates the fourth sub-weight omega ^ occupied by each evaluation index in the key component by an entropy weight method, wherein the omega ^ specifically is,
ω^＝[0.1474,0.0848,0.0921,0.0847,0.0850,,0.1474,0.1474,0.0638,0.1474]
the server leads the third sub-weight and the fourth sub-weight to pass through a formula omega-theta omega*And + (1-theta) omega ^ is subjected to weighted summation to obtain a first weight omega, and theta is the weight occupied by the analytic hierarchy process in the weighted summation process. Wherein omega is specifically the group consisting of,
ω＝[0.1087,0.0667,0.0750,0.0745,0.0816,0.1354,0.1498,0.1114,0.1968]
the server generates a first matrix according to the obtained first weight, wherein the first matrix is as follows:
W1＝[0.1087,0.0667,0.0750,0.0745,0.0816,0.1354,0.1498,0.1114,0.1968]
step 104: and converting the membership degree value into an evaluation value, and converting the evaluation value into a fuzzy matrix by a fuzzy comprehensive evaluation method.
In the embodiment of the application, after obtaining the membership degree value of each index to be evaluated, the server calculates the second weight occupied by each evaluation index in the affiliated key component, converts the membership degree value and the second weight into the evaluation value through fuzzy change, and then converts the evaluation value into the fuzzy matrix W through a fuzzy comprehensive evaluation method2Wherein the matrix W is blurred2Is composed of
Step 105: and generating a plurality of target evaluation values of the device through the first matrix and the fuzzy matrix, and selecting an evaluation result corresponding to the maximum target evaluation value from the plurality of target evaluation values as a target evaluation result according to the corresponding relation between the target evaluation values and the evaluation result.
In the embodiment of the application, the server combines the first matrix W1And a fuzzy matrix W2Multiplying, generating a target matrix of the device, wherein the target matrix comprises a plurality of target evaluation values, each target evaluation value corresponds to an evaluation result, and the server selects the largest target evaluation value from the plurality of target evaluation values and takes the evaluation result corresponding to the target evaluation value as the target evaluation result.
The results of the state of health target assessment of the integrated transmission are shown in table two:
watch two
As can be seen from table two, the integrated transmission has five target evaluation values, each corresponding to an evaluation result. The maximum target evaluation value is 0.4679, the evaluation result corresponding to 0.4679 is scrapped, and the target evaluation result of the comprehensive transmission device is scrapped.
Optionally, the server converts the membership value into an evaluation value, as shown in fig. 3, including:
step 201: and calculating a second weight of each evaluation index in the key part.
In this embodiment of the present application, the process of calculating, by the server, the second weight occupied by each evaluation index in the related key component is as follows: the server calculates the first sub-weight of each evaluation index in the key component through an analytic hierarchy process; the server calculates a second sub-weight of each evaluation index in the key component by an entropy weight method; and the server performs weighted summation on the first sub-weight and the second sub-weight to obtain a second weight.
In the embodiment of the application, the server calculates the first sub-weight of each evaluation index in the related key component by an analytic hierarchy process, as follows:
wherein,
to
And respectively representing the third sub-weight occupied by the nine key components in the evaluation index system.
The server calculates the fourth sub-weight of each evaluation index in the key component by an entropy weight method, as follows:
wherein,
to
Respectively representing the fourth sub-weight occupied by the nine key components in the evaluation index system.
The server passes the third sub-weight and the fourth sub-weight through a formula
The weighted sum is performed to obtain a first weight, as follows:
ω1＝[0.0453,0.4058,0.2455,0.0811,0.2223]
ω2＝[0.0597,0.0170,0.2495,0.2607,0.1732,0.2398]
ω3＝[0.0923,0.6429,0.2647]
ω4＝[0.4483,0.1759,0.0415,0.3342]
ω5＝[0.1425,0.2991,0.2202,0.3381]
ω6＝[0.1028,0.0894,0.8079]
ω7＝[0.4293,0.5707]
ω8＝[0.4504,0.1350,0.0759,0.1770,0.1617]
ω9＝[0.4129,0.5871]
wherein, ω is1To omega9Respectively show nine key components in the commentEstimating a first weight occupied in the index system.
Step 202: and converting the membership value and the second weight into an evaluation value through fuzzy change.
For example, the server converts the membership value and the second weight into an evaluation value through fuzzy change, and the evaluation value of each key component is shown in table three:
watch III
The server selects the largest evaluation value from the plurality of evaluation values of each key component, takes the evaluation result corresponding to the evaluation value as the analysis result of the key component, and the analysis result is used for representing the health state of the key component and can be used for analyzing the health state of the comprehensive transmission device.
Based on the same technical concept, the embodiment of the present application further provides an apparatus evaluation apparatus, as shown in fig. 4, the apparatus including:
the establishing module 301 is configured to establish an evaluation index system of the apparatus, and receive a parameter value of an index to be evaluated, which is generated in an operation process of the apparatus, where the evaluation index system includes a plurality of key components, and each of the key components includes a plurality of indexes to be evaluated;
an input/output module 302, configured to input the parameter value into a membership function, and output a membership value of each to-be-evaluated index;
a calculating module 303, configured to calculate a first weight occupied by each of the key components in the evaluation index system, and generate a first matrix from all the first weights;
the conversion module 304 is configured to convert the membership value into an evaluation value, and convert the evaluation value into a fuzzy matrix by a fuzzy comprehensive evaluation method;
a generating module 305, configured to generate a plurality of target evaluation values of the apparatus through the first matrix and the fuzzy matrix, and select an evaluation result corresponding to a largest target evaluation value from the plurality of target evaluation values as a target evaluation result according to a correspondence between the target evaluation values and the evaluation result.
Optionally, the conversion module 304 includes:
the calculating unit is used for calculating a second weight of each evaluation index in the key component;
and the conversion unit is used for converting the membership degree value and the second weight into the evaluation value through fuzzy change.
Optionally, the computing unit includes:
the first calculating unit is used for calculating a first sub weight of each evaluation index in the key component through an analytic hierarchy process;
the second calculating unit is used for calculating a second sub weight occupied by each evaluation index in the key component through an entropy weight method;
and the third calculating unit is used for carrying out weighted summation on the first sub-weight and the second sub-weight to obtain the second weight.
Optionally, the generating module 305 includes:
and the generating unit is used for generating a target matrix through the product of the first matrix and the fuzzy matrix and taking a plurality of elements in the target matrix as the plurality of target numerical values.
Optionally, the apparatus further comprises:
and the selecting module is used for selecting the evaluation result corresponding to the largest evaluation numerical value from the evaluation numerical values according to the corresponding relation between the evaluation numerical value and the evaluation result in each key component as the analysis result in each key component, wherein the analysis result represents the health state of the key component.
Optionally, the calculation module includes:
the fourth calculating unit is used for calculating a third sub-weight of each key component in the evaluation index system through an analytic hierarchy process;
the fifth calculating unit is used for calculating a fourth sub-weight occupied by each evaluation index in the key component through an entropy weight method;
and the sixth calculating unit is used for weighting and summing the third sub-weight and the fourth sub-weight to obtain the first weight.
The embodiment of the application provides a device evaluation method, the method converts the parameter value of the index to be evaluated into a target evaluation value of the device, and selects the evaluation result corresponding to the largest value in the target evaluation values as the target evaluation result according to the corresponding relation between the target evaluation value and the evaluation result, the evaluation result is simple and clear, in addition, the method combines an analytic hierarchy process and an entropy weight process, and the reasonability of the result is ensured.
Based on the same technical concept, the embodiment of the present invention further provides an electronic device, as shown in fig. 5, including a processor 401, a communication interface 402, a memory 403 and a communication bus 404, where the processor 401, the communication interface 402, and the memory 403 complete mutual communication through the communication bus 404,
a memory 403 for storing a computer program;
the processor 401, when executing the program stored in the memory 403, implements the above method steps.
The communication bus mentioned in the electronic device may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the electronic equipment and other equipment.
The Memory may include a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components.
In a further embodiment provided by the present invention, a computer-readable storage medium is also provided, in which a computer program is stored, which, when being executed by a processor, carries out the above-mentioned method steps.
In a further embodiment provided by the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform any of the methods of the above embodiments.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, 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 identical elements in a process, method, article, or apparatus that comprises the element.
The above description is merely exemplary of the present application and is presented to enable those skilled in the art to understand and practice the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for device evaluation, the method comprising:
establishing an evaluation index system of the device, and receiving parameter values of indexes to be evaluated generated in the running process of the device, wherein the evaluation index system comprises a plurality of key components, and each key component comprises a plurality of indexes to be evaluated;
inputting the parameter values into a membership function, and outputting a membership numerical value of each index to be evaluated;
calculating a first weight of each key component in the evaluation index system, and generating a first matrix from all the first weights;
converting the membership numerical value into an evaluation numerical value, and converting the evaluation numerical value into a fuzzy matrix by a fuzzy comprehensive evaluation method;
and selecting an evaluation result corresponding to the maximum target evaluation value from the plurality of target evaluation values as a target evaluation result according to the corresponding relation between the target evaluation values and the evaluation result through the plurality of target evaluation values of the first matrix and the fuzzy matrix generation device.
2. The method of claim 1, wherein converting the membership value to an evaluation value comprises:
calculating a second weight of each evaluation index in the key part;
and converting the membership grade value and the second weight into the evaluation value through fuzzy change.
3. The method according to claim 2, wherein the calculating of the second weight of each evaluation index in the key component comprises:
calculating a first sub-weight of each evaluation index in the key component by an analytic hierarchy process;
calculating a second sub-weight of each evaluation index in the key part by an entropy weight method;
and carrying out weighted summation on the first sub-weight and the second sub-weight to obtain the second weight.
4. The method of claim 1, wherein generating the plurality of target values for the device using the first matrix and the blur matrix comprises:
and generating a target matrix through the product of the first matrix and the fuzzy matrix, and taking a plurality of elements in the target matrix as the plurality of target numerical values.
5. The method of claim 1, wherein after converting the membership value to an evaluation value, further comprising:
and selecting the evaluation result corresponding to the maximum evaluation numerical value from the evaluation numerical values according to the corresponding relation between the evaluation numerical value and the evaluation result in each key component as the analysis result in each key component, wherein the analysis result represents the health state of the key component.
6. The method of claim 1, wherein calculating the first weight of each of the key components in the evaluation index system comprises:
calculating a third sub-weight of each key component in the evaluation index system by an analytic hierarchy process;
calculating the fourth sub-weight of each evaluation index in the key part by an entropy weight method;
and carrying out weighted summation on the third sub-weight and the fourth sub-weight to obtain the first weight.
7. An apparatus evaluation apparatus, characterized in that the apparatus comprises:
the device comprises an establishing module, a judging module and a judging module, wherein the establishing module is used for establishing an evaluation index system of the device and receiving parameter values of indexes to be evaluated generated in the running process of the device, the evaluation index system comprises a plurality of key components, and each key component comprises a plurality of indexes to be evaluated;
the input and output module is used for inputting the parameter values into a membership function and outputting the membership numerical value of each index to be evaluated;
the calculation module is used for calculating a first weight occupied by each key component in the evaluation index system and generating a first matrix from all the first weights;
the conversion module is used for converting the membership numerical value into an evaluation numerical value and converting the evaluation numerical value into a fuzzy matrix through a fuzzy comprehensive evaluation method;
and the generating module is used for generating a plurality of target evaluation values of the device through the first matrix and the fuzzy matrix, and selecting an evaluation result corresponding to the largest target evaluation value from the plurality of target evaluation values as a target evaluation result according to the corresponding relation between the target evaluation values and the evaluation result.
8. The apparatus of claim 7, wherein the conversion module comprises:
the calculating unit is used for calculating a second weight of each evaluation index in the key component;
and the conversion unit is used for converting the membership degree value and the second weight into the evaluation value through fuzzy change.
9. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing mutual communication by the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any of claims 1-6 when executing a program stored in the memory.
10. A computer-readable storage medium, characterized in that a computer program is stored in the computer-readable storage medium, which computer program, when being executed by a processor, carries out the method steps of any one of claims 1 to 6.
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