Product evaluation method based on capability quantification and computer readable storage medium

Abstract

The invention provides a product evaluation method based on capability quantification, and the method comprises the steps: building a capability quantification index system according to the indexes of a product to be evaluated; secondly, according to the function requirement of a user on the product, selecting an evaluation index corresponding to the function requirement of the product needing to be evaluated from the capability quantitative index system; then, the weight proportion of the single evaluation index in the capability value is obtained; moreover, normalization processing is carried out on the evaluation indexes, and then a normalization result of the evaluation indexes is obtained. And then, according to the weight ratio of the evaluation indexes of the product and the normalization result of the evaluation indexes, obtaining the quantized value of the product capability. And on this basis, a second capability quantized value of the system is obtained based on the first capability quantized value and the product weight, and the capability of the system is evaluated based on the second quantized value.

Description

Technical Field

[0001] The present invention relates to the field of evaluation methods, and more particularly, to a product evaluation method based on ability quantification. Background Art

[0002] Currently, in the prior art, in the field of complex system integration, the prior art generally faces the evaluation dilemma of cross-brand and cross-protocol device collaborative work. Taking a satellite constellation as an example, when the system consists of heterogeneous devices from multiple manufacturers (such as on-board computers, propulsion modules, payload units), the traditional evaluation dimensions are too single, lacking quantitative evaluation of product ability characteristics and system indicators. Summary of the Invention

[0003] The present invention aims to solve at least one of the technical problems existing in the prior art or related technologies.

[0004] To this end, a first aspect of the present invention provides a product evaluation method based on ability quantification.

[0005] A second aspect of the present invention provides a computer-readable storage medium.

[0006] In view of this, a first aspect of the present invention provides a product evaluation method based on ability quantification, including: establishing a product ability quantification index system based on the product's indicators; selecting the corresponding evaluation indicators of the product in the ability quantification index system based on the product's functional requirements; obtaining the weight ratio of the evaluation indicators based on the evaluation indicators; performing normalization processing on the evaluation indicators to obtain the normalization result of the evaluation indicators; obtaining the first ability quantification value of the product based on the weight ratio and the normalization result; obtaining the second ability quantification value of the system based on the first ability quantification value and the product weight, and evaluating the ability of the system based on the second quantification value.

[0007] In addition, the product evaluation method based on ability quantification provided by the above technical solution of the present invention may further have the following additional technical features: In some technical solutions of the present invention, optionally, establishing a product ability quantification index system based on the product's indicators includes: obtaining the product's indicators; classifying the product's indicators based on the product's performance, and establishing an ability quantification index system.

[0008] In some technical solutions of the present invention, optionally, obtaining the weight ratio of the evaluation indicators based on the evaluation indicators includes: setting the relative importance parameter of the same evaluation indicators of two products based on the same evaluation indicators of the two products; constructing a judgment matrix based on the same evaluation indicators and the relative importance parameter of the two products; obtaining the maximum eigenvalue and the eigenvector under the maximum eigenvalue of the judgment matrix based on the judgment matrix; performing a consistency test on the judgment matrix, and if the judgment matrix passes the verification, selecting the eigenvector as the weight ratio of the evaluation indicators.

[0009] In some technical solutions of the present invention, optionally, a consistency test is performed on the judgment matrix. If the judgment matrix passes the verification, the eigenvector is selected as the weight ratio of the evaluation index, including: obtaining a consistency index based on the largest eigenvalue and the order of the judgment matrix; obtaining an average random consistency index based on the eigenvalues of the judgment matrix; obtaining a consistency ratio based on the consistency index and the average random consistency index. If the consistency ratio is lower than a preset threshold, the eigenvector is selected as the weight ratio of the evaluation index.

[0010] In some technical solutions of the present invention, optionally, a normalization process is performed on the evaluation index to obtain the normalized result of the evaluation index, including: determining whether the evaluation index has a linear relationship with the product performance. If the evaluation index has a linear relationship with the product performance, determining the first monotonic trend of the evaluation index and the product performance, and obtaining the normalized result of the evaluation index based on the first monotonic trend; otherwise, determining the second monotonic trend of the evaluation index and the product performance, and obtaining the normalized result of the evaluation index based on the second monotonic trend.

[0011] In some technical solutions of the present invention, optionally, if the evaluation index has a linear relationship with the product performance, determining the first monotonic trend of the evaluation index and the product performance, and obtaining the normalized result of the evaluation index based on the first monotonic trend, including: if the first monotonic trend of the evaluation index and the product performance is an increasing trend, obtaining the normalized result of the evaluation index based on the original value of the evaluation index and the minimum value of the evaluation index; if the first monotonic trend of the evaluation index and the product performance is a decreasing trend, obtaining the normalized result of the evaluation index based on the original value of the evaluation index and the maximum value of the evaluation index.

[0012] In some technical solutions of the present invention, optionally, determining the second monotonic trend of the evaluation index and the product performance, and obtaining the normalized result of the evaluation index based on the second monotonic trend, including: if the second monotonic trend of the evaluation index and the product performance is an increasing trend, obtaining the normalized result of the evaluation index based on the original value of the evaluation index and the maximum value of the evaluation index; if the second monotonic trend of the evaluation index and the product performance is a decreasing trend, obtaining the normalized result of the evaluation index based on the original value of the evaluation index and the minimum value of the evaluation index.

[0013] The second aspect of the present invention provides a computer-readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the product evaluation method based on ability quantification in any of the above technical solutions is implemented.

[0014] The product evaluation method based on ability quantification proposed by the present invention presents a three - layer design framework for quantitative characterization, which can serve as the basic basis for product and system ability analysis, combat method research, and selection of equipment in the system composition. It helps to eliminate subjective differences among different evaluators, improves the evaluation efficiency, and ensures the objectivity and accuracy of the evaluation results.

[0015] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above - mentioned and / or additional aspects and advantages of the present invention will become apparent and be readily understood from the description of the embodiments in conjunction with the following drawings, wherein: Figure 1 FIG. is a flowchart of a product evaluation method based on ability quantification according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] In order to more clearly understand the above - mentioned objects, features, and advantages of the present invention, the present invention will be further described in detail below in conjunction with the drawings and specific embodiments. It should be noted that, without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other.

[0018] Many specific details are set forth in the following description in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited by the specific embodiments disclosed below.

[0019] Next, refer to Figure 1 Describe a product evaluation method based on ability quantification and a computer - readable storage medium according to some embodiments of the present invention.

[0020] As Figure 1 shown, the first aspect of the present invention provides a product evaluation method based on ability quantification, including: Step 102, establish an ability quantification index system for the product based on the product's indicators; Step 104, select the corresponding evaluation indicators for the product in the ability quantification index system based on the functional requirements of the product; Step 106, obtain the weight ratio of the evaluation indicators based on the evaluation indicators; Step 108, perform normalization processing on the evaluation indicators to obtain the normalization result of the evaluation indicators; Step 110, obtain the first ability quantification value of the product based on the weight ratio and the normalization result; Step 112: Obtain the second ability quantification value of the system based on the first ability quantification value and the product weight, and evaluate the ability of the system based on the second quantification value.

[0021] The present invention proposes a product evaluation method based on ability quantification. First, establish an ability quantification index system according to the indicators of the product to be evaluated. Among them, the ability quantification index system is a system constructed by the indicators that will be quantified when evaluating the product ability.

[0022] Secondly, according to the functional requirements of the user for the product, select the evaluation indicators corresponding to the functional requirements of the product to be evaluated from the ability quantification index system.

[0023] Then, obtain the weight ratio of this single evaluation indicator in this ability value. And perform normalization processing on the evaluation indicator to obtain the normalized result of the evaluation indicator.

[0024] After that, first obtain the quantification value of the product ability, that is, the first ability quantification value of the product, according to the weight ratio of the evaluation indicators of the product and the normalized result of the evaluation indicator. On this basis, because the working mode of some products requires multiple products to form a system. For example, in the aerospace system, the satellite constellation is composed of multiple satellites, and due to the different numbers and tasks, the importance of different satellites is also different. Therefore, based on the first ability quantification value and the product weight, obtain the second ability quantification value of the system, and evaluate the ability of the system based on the second quantification value.

[0025] The present invention realizes the ability evaluation from a single product to a complex system by establishing a multi-level quantification evaluation system, transforms the abstract user requirements into quantifiable technical indicators, solves the problem of disconnection between requirements and evaluation, breaks through the limitation of single product evaluation, and supports the comprehensive ability calculation of multi-product collaborative systems (such as a constellation system composed of 12 satellites, reflecting the value difference between primary and backup satellites through different weight distributions). Through the construction of a refined index system, weight allocation, and normalization processing, the evaluation results are more accurate, can truly reflect the actual ability of the product, improve the flexibility of evaluation, provide an effective means for the ability evaluation of complex systems, and improve the decision-making efficiency.

[0026] Specifically, the ability quantification index system is established according to the static attributes in the indicators.

[0027] Further, in some embodiments of the present invention, based on the indicators of the product, establish an ability quantification index system of the product, including: obtaining the indicators of the product; classifying the indicators of the product based on the performance of the product, and establishing an ability quantification index system.

[0028] In this embodiment, first, obtain the indicators of the product. Then classify the indicators of the product according to the performance of the product, establish a capacity quantification index system, and establish an association between the corresponding indicators and the corresponding performance.

[0029] Table 1 Capacity Quantification Index System of Remote Sensing Satellites In one specific embodiment, as shown in Table 1, when it is necessary to evaluate the intelligence of a remote sensing satellite, the panchromatic resolution is one of the evaluation indicators. After establishing the capacity quantification index system, the evaluation indicators corresponding to the performance can be selected from the capacity quantification index system. It should be noted that although there are the same evaluation indicators in different performances, this does not affect the subsequent evaluation. Because a single evaluation indicator may have different weight ratios in the evaluation due to different performances.

[0030] By constructing a capacity quantification index system, the various performance indicators of the remote sensing satellite are systematically organized, providing a clear and orderly framework for the subsequent evaluation work. According to the specific performance requirements for product evaluation, the corresponding evaluation indicators are selected from the index system, ensuring the pertinence and accuracy of the evaluation work. At the same time, it is allowed to have the same evaluation indicators in different performances, but the weight ratio is adjusted according to different performances, reflecting the flexibility of the evaluation method and its adaptability to different situations, reducing the redundancy and repetitive work in the evaluation process, improving the evaluation efficiency, ensuring the accuracy and reliability of the evaluation results, and improving the quality and effect of decision-making.

[0031] Furthermore, in some embodiments of the present invention, based on the evaluation indicators, obtain the weight ratio of the evaluation indicators, including: setting the relative importance parameter of the same evaluation indicators of two products based on the same evaluation indicators of the two products; constructing a judgment matrix based on the same evaluation indicators and relative importance parameters of the two products; obtaining the maximum eigenvalue and the eigenvector corresponding to the maximum eigenvalue of the judgment matrix based on the judgment matrix; performing a consistency test on the judgment matrix, and if the judgment matrix passes the verification, select the eigenvector as the weight ratio of the evaluation indicators.

[0032] In this embodiment, first, select the same evaluation indicators of two products, and determine the relative importance parameter of the two products under this same evaluation indicator according to the actual situations of the two products.

[0033] Secondly, pairwise comparison of the same evaluation indicators of the two products can construct a judgment matrix, and the specific parameters in the judgment matrix are substituted by the relative importance parameter.

[0034] Then, obtain the eigenvector and the maximum eigenvalue of the judgment matrix, and conduct a consistency test on the judgment matrix. If the judgment matrix passes the verification, select the eigenvector as the weight ratio of the evaluation indicators.

[0035] This embodiment realizes the scientific quantification of the index weights through the analytic hierarchy process, converts the numerical values into computable numerical parameters, automatically identifies logical contradictions through the matrix consistency test, improves the accuracy and reliability of decision-making, reduces the decision-making cost caused by subjective biases, and improves the efficiency of decision-making.

[0036] Table 2 Relative importance parameters Specifically, the representation method of the relative importance parameters of the same evaluation indicators of two products is as follows: . Among them, is an evaluation indicator of one of the products for the evaluation indicator of another product of the relative importance parameter, is an evaluation indicator of another product for the evaluation indicator of one of the products of the relative importance parameter.

[0037] Specifically, the eigenvector of the judgment matrix is calculated separately by using the "sum-product method" and the "root method". The eigenvectors of the judgment matrix calculated separately by using the "sum-product method" and the "root method" should have good consistency, and the difference should not be greater than the first threshold. Either the "sum-product method" or the "root method" can be used.

[0038] Furthermore, in some embodiments of the present invention, when conducting a consistency test on the judgment matrix, if the judgment matrix passes the verification, selecting the eigenvector as the weight ratio of the evaluation indicators includes: obtaining a consistency index based on the maximum eigenvalue and the order of the judgment matrix; obtaining an average random consistency index based on the eigenvalues of the judgment matrix; obtaining a consistency ratio based on the consistency index and the average random consistency index. If the consistency ratio is lower than the preset threshold, then select the eigenvector as the weight ratio of the evaluation indicators.

[0039] In this embodiment, first, obtain a consistency index based on the maximum eigenvalue and the order of the judgment matrix.

[0040] Then, because there may be multiple eigenvalues in the judgment matrix in addition to the maximum eigenvalue, obtain an average random consistency index based on the eigenvalues of the judgment matrix.

[0041] Subsequently, divide the consistency index by the average random consistency index to obtain the consistency ratio. If the consistency ratio is lower than the preset threshold, select the eigenvector as the weight ratio of the evaluation index.

[0042] By calculating the consistency index and the average random consistency index and comparing their magnitude relationship (i.e., the consistency ratio), the consistency and logic of the judgment matrix can be tested. When the consistency ratio is lower than the preset threshold, the judgment matrix is considered to have satisfactory consistency, thus ensuring the quality of the evaluation.

[0043] Specifically, the calculation formula for the consistency index is: . Wherein, is the consistency index, is the maximum eigenvalue, is the order of the judgment matrix.

[0044] Specifically, the calculation method for the consistency ratio is: . Wherein, is the consistency ratio, is the average random consistency index. When , generally, the consistency of the judgment matrix is considered acceptable.

[0045] Specifically, the eigenvector obtained by either the "sum-product method" or the "root method" can be arbitrarily selected as the index weight.

[0046] It can be understood that the method for obtaining the product weight is the same as that for the weight ratio of the evaluation index. Among them, the method for obtaining the product index is: based on the same ability indexes of two products, set the relative importance parameters of the same ability indexes of the two products; based on the same ability indexes and relative importance parameters of the two products, construct a judgment matrix; based on the judgment matrix, obtain the eigenvector and the maximum eigenvalue of the judgment matrix; based on the maximum eigenvalue and the order of the judgment matrix, obtain the consistency index; based on the eigenvalues of the judgment matrix, obtain the average random consistency index; based on the consistency index and the average random consistency index, obtain the consistency ratio. If the consistency ratio is lower than the preset threshold, select the eigenvector as the product index.

[0047] Furthermore, in some embodiments of the present invention, the evaluation index is normalized to obtain the normalized result of the evaluation index, including: determining whether the evaluation index has a linear relationship with the product performance. If the evaluation index has a linear relationship with the product performance, determine the first monotonic trend of the evaluation index and the product performance, and obtain the normalized result of the evaluation index based on the first monotonic trend; otherwise, determine the second monotonic trend of the evaluation index and the product performance, and obtain the normalized result of the evaluation index based on the second monotonic trend.

[0048] In this embodiment, to determine the relationship between the evaluation index and the product performance, first, it is judged whether there is a linear relationship between the evaluation index and the product performance, and then the monotonic trend of the evaluation index and the product performance is further judged, so as to further process the data and obtain a normalized structure. Through the comprehensive analysis and processing of the relationship between the evaluation index and the product performance, a more accurate evaluation result can be obtained. This helps enterprises formulate more effective product optimization strategies and market decisions.

[0049] Further, in some embodiments of the present invention, if there is a linear relationship between the evaluation index and the product performance, judge the first monotonic trend of the evaluation index and the product performance, and obtain the normalized result of the evaluation index based on the first monotonic trend, including: if the first monotonic trend of the evaluation index and the product performance is an increasing trend, obtain the normalized result of the evaluation index based on the original value of the evaluation index and the minimum value of the evaluation index; if the first monotonic trend of the evaluation index and the product performance is a decreasing trend, obtain the normalized result of the evaluation index based on the original value of the evaluation index and the maximum value of the evaluation index.

[0050] In this embodiment, if the first monotonic trend of the evaluation index and the product performance is an increasing trend, obtain the normalized result of the evaluation index based on the original value of the evaluation index and the minimum value of the evaluation index.

[0051] If the first monotonic trend of the evaluation index and the product performance is a decreasing trend, obtain the normalized result of the evaluation index based on the original value of the evaluation index and the maximum value of the evaluation index.

[0052] Table 3 Normalization method for linear indicators Specifically, is the normalized result of the evaluation index, is the original value of the evaluation index, is the minimum value of the evaluation index, is the maximum value of the evaluation index.

[0053] Further, in some embodiments of the present invention, judge the second monotonic trend of the evaluation index and the product performance, and obtain the normalized result of the evaluation index based on the second monotonic trend, including: if the second monotonic trend of the evaluation index and the product performance is an increasing trend, obtain the normalized result of the evaluation index based on the original value of the evaluation index and the maximum value of the evaluation index; if the second monotonic trend of the evaluation index and the product performance is a decreasing trend, obtain the normalized result of the evaluation index based on the original value of the evaluation index and the minimum value of the evaluation index.

[0054] In this embodiment, if the second monotonic trend of the evaluation index and the product performance is an increasing trend, obtain the normalized result of the evaluation index based on the original value of the evaluation index and the maximum value of the evaluation index.

[0055] If the second monotonic trend between the evaluation index and the product performance is a decreasing trend, based on the original value of the evaluation index and the minimum value of the evaluation index, obtain the normalization result of the evaluation index.

[0056] Table 4 Normalization Method for Nonlinear Indexes Specifically, the calculation formula for the first ability quantization value is: 。

[0057] Wherein, is the first ability quantization value of the i-th ability of the product, is the index weight corresponding to the t-th evaluation index of the i-th ability of the product, represents the normalization result of the t-th evaluation index under a certain ability.

[0058] Specifically, the calculation formula for the second ability quantization value is: 。

[0059] Wherein, is the second ability quantization value of the y-th system, is the product weight of the i-th product of the y-th system, represents the quantity of the i-th product in the y-th system.

[0060] The second aspect of the present invention provides a computer-readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, it implements the product evaluation method based on ability quantization in any of the above embodiments, and thus has all the beneficial technical effects of the product evaluation method based on ability quantization in any of the above embodiments.

[0061] Wherein, the computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc.

[0062] A computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer-readable storage medium can be an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above devices, but is not limited thereto. A non-exhaustive list of more specific examples of computer-readable storage media includes: portable computer floppy disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, static random access memories, portable compact disc read-only memories, digital versatile discs, memory cards, floppy disks, encoding mechanical devices (such as punched cards or grooves with raised structures recording instructions), and any suitable combination of the above devices. The computer-readable storage medium used herein should not be construed as a transmission signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media, or electrical signals transmitted through wires, etc.

[0063] In one specific embodiment, the workflow of the product evaluation method based on ability quantification proposed by the present invention is as follows: First, obtain the product's metrics. And classify the product's metrics according to the product's performance, establish an ability quantification metric system, and establish an association between the corresponding metrics and the corresponding performance. Among them, the ability quantification metric system is a system constructed for the metrics that will be quantified when evaluating the product's ability.

[0064] Second, according to the user's functional requirements for the product, select the evaluation metrics corresponding to the functional requirements of the product to be evaluated from the ability quantification metric system.

[0065] Then, select the same evaluation metrics for two products, and determine the relative importance parameters of the two products under this same evaluation metric according to the actual situations of the two products. Pairwise comparison of the same evaluation metrics of the two products can construct a judgment matrix, where the specific parameters in the judgment matrix are substituted by the relative importance parameters. Based on the maximum eigenvalue and the order of the judgment matrix, obtain the consistency index. Since there may be multiple eigenvalues in the judgment matrix in addition to the maximum eigenvalue, based on the eigenvalues of the judgment matrix, obtain the average random consistency index. Divide the consistency index by the average random consistency index to obtain the consistency ratio. If the consistency ratio is lower than the preset threshold, select the eigenvector as the weight ratio of the evaluation metrics.

[0066] Subsequently, first, according to the weight ratio of the evaluation indicators of the product and the normalization result of the evaluation indicators, a quantitative value of the product's ability is obtained, that is, the first ability quantitative value of the product. On this basis, since the working mode of some products requires a system composed of multiple products. For example, a space system is composed of multiple satellites, and due to the differences in quantity and tasks, the importance of different satellites also varies. Therefore, based on the first ability quantitative value and the product weight, a second ability quantitative value of the system is obtained, and the ability of the system is evaluated based on the second quantitative value.

[0067] In the claims, the description and the accompanying drawings of the present invention, the term "a plurality" means two or more, unless otherwise expressly limited. The orientation or positional relationship indicated by terms such as "upper", "lower", etc. is based on the orientation or positional relationship shown in the drawings. It is only for more convenient description of the present invention and to simplify the description process, rather than to indicate or imply that the device or element referred to must have the specific orientation, be constructed and operated in the specific orientation. Therefore, these descriptions should not be construed as limitations on the present invention; terms such as "connection", "installation", "fixation", etc. should all be understood in a broad sense. For example, "connection" can be a fixed connection between multiple objects, a detachable connection between multiple objects, or an integral connection; it can be a direct connection between multiple objects, or an indirect connection between multiple objects through an intermediate medium. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances of the above data.

[0068] In the claims, the description and the accompanying drawings of the present invention, the description of terms such as "one embodiment", "some embodiments", "specific embodiments", etc. mean that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In the claims, the description and the accompanying drawings of the present invention, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0069] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A product evaluation method based on capability quantification, characterized in that: include: Based on product indicators, establish a product capability quantitative indicator system; Based on the functional requirements of the product, select the evaluation indicators corresponding to the product in the capability quantitative indicator system; Based on the evaluation indicators, obtain the weight ratio of the evaluation indicators; Normalize the evaluation index to obtain the normalized result of the evaluation index; Based on the weight ratio and the normalization result, obtaining a first capability quantization value of the product; Based on the first capability quantification value and the product weight, a second capability quantification value of the system is acquired, and the capability of the system is evaluated based on the second capability quantification value.

2. The product evaluation method based on capability quantification according to claim 1 is characterized in that: The product-based indicators establish a product capability quantitative indicator system, including: Obtaining metrics for said product; Based on the performance of the product, the indicators of the product are classified and the capability quantification indicator system is established.

3. The product evaluation method based on capability quantification according to claim 1, characterized in that: The step of obtaining the weight ratio of the evaluation index based on the evaluation index includes: Based on the same evaluation indicators of the two products, set the relative importance parameters of the same evaluation indicators of the two products; Based on the same evaluation indicators of the two products and the relative importance parameters, a judgment matrix is ​​constructed; Based on the judgment matrix, obtaining the maximum eigenvalue of the judgment matrix and the eigenvector under the maximum eigenvalue; A consistency check is performed on the judgment matrix. If the judgment matrix passes the verification, the eigenvector is selected as the weight ratio of the evaluation index.

4. The product evaluation method based on capability quantification according to claim 3 is characterized in that: The performing consistency check on the judgment matrix, and if the judgment matrix passes the verification, selecting the eigenvector as the weight ratio of the evaluation index, comprises: Obtaining a consistency index based on the maximum eigenvalue and the order of the judgment matrix; Based on the eigenvalues ​​of the judgment matrix, obtaining an average random consistency index; Based on the consistency index and the average random consistency index, a consistency ratio is obtained. If the consistency ratio is lower than a preset threshold, the feature vector is selected as the weight ratio of the evaluation index.

5. The product evaluation method based on capability quantification according to claim 1, characterized in that: The normalizing the evaluation index to obtain the normalized result of the evaluation index includes: Determine whether the evaluation index is linearly related to the product performance, and if so, determine a first monotonic trend between the evaluation index and the product performance, and obtain a normalized result of the evaluation index based on the first monotonic trend; Otherwise, a second monotonic trend between the evaluation index and the product performance is determined, and a normalized result of the evaluation index is obtained based on the second monotonic trend.

6. The product evaluation method based on capability quantification according to claim 5 is characterized in that: If the evaluation index is linearly related to the product performance, determining a first monotonic trend between the evaluation index and the product performance, and obtaining a normalized result of the evaluation index based on the first monotonic trend, comprises: If the first monotonic trend of the evaluation index and the product performance is an increasing trend, obtaining a normalized result of the evaluation index based on the original value of the evaluation index and the minimum value of the evaluation index; If the first monotonic trend of the evaluation index and the product performance is a decreasing trend, a normalized result of the evaluation index is obtained based on an original value of the evaluation index and a maximum value of the evaluation index.

7. The product evaluation method based on capability quantification according to claim 5 is characterized in that: The determining a second monotonic trend between the evaluation index and the product performance, and obtaining a normalized result of the evaluation index based on the second monotonic trend, includes: If the second monotonic trend of the evaluation index and the product performance is an increasing trend, obtaining a normalized result of the evaluation index based on the original value of the evaluation index and the maximum value of the evaluation index; If the second monotonic trend of the evaluation index and the product performance is a decreasing trend, a normalized result of the evaluation index is obtained based on the original value of the evaluation index and the minimum value of the evaluation index.

8. A computer-readable storage medium storing a program or an instruction, characterized in that: When the program or the instruction is executed by a processor, the product evaluation method based on capability quantification according to any one of claims 1 to 7 is implemented.

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