WO2021073065A1

WO2021073065A1 - Technical index digitalization method and apparatus, computer device and storage medium

Info

Publication number: WO2021073065A1
Application number: PCT/CN2020/085905
Authority: WO
Inventors: 沈象文
Original assignee: 深圳壹账通智能科技有限公司
Priority date: 2019-10-16
Filing date: 2020-04-21
Publication date: 2021-04-22
Also published as: CN111027020A

Abstract

The embodiments of the present application relate to the field of big data, and relates to a technical index digitalization method and apparatus, a device and a storage medium. The method comprises: determining technical indexes in a scoring standard according to a requirement goal, decomposing the technical indexes according to hierarchies, and building a step hierarchy structure in a database; corresponding to the same technical index in the previous hierarchy, comparing the importance of the technical indexes in the next hierarchy pairwise, and outputting a digitized judgment matrix; calculating the relative weight of the compared technical indexes with respect to the technical indexes of the previous hierarchy according to the judgment matrix, and calculating the weight of the technical indexes of each hierarchy to the goal according to the relative weight; and when the judgment matrix passes a consistency check, calculating scores according to the technical indexes of each hierarchy and the corresponding weights, and storing the scores in the database. In the present application, technical indexes are no longer determined artificially, and subjective judgment is digitized; in addition, a solution of a mathematical model is provided, and consistency inspection is supported.

Description

Technical index data processing method, device, computer equipment and storage medium

This application claims the priority of a Chinese patent application filed with the Chinese Patent Office on October 16, 2019, the application number is 201910981531.6, and the invention title is "Technical Index Data Processing Methods, Devices, Computer Equipment, and Storage Media", and its entire contents Incorporated in this application by reference.

Technical field

This application relates to the field of big data technology, and in particular to methods, devices, computer equipment, and storage media for data processing of technical indicators.

Background technique

The scoring standards used in the rapid integration of the technology section mainly involve technical indicators and corresponding weights. At present, the manager artificially determines the technical indicators and corresponding weights according to the needs and goals of the rapid integration of each technical section, and with their own experience, the inventor realizes that this is bound to have the following defects:

1. The scoring standard is relatively independent, and the scoring standard needs to be re-developed every time the technical section is quickly integrated;

2. The selection of technical indicators and the determination of corresponding weights are often determined by humans, lacking theoretical support, and highly subjective;

3. The correlation and influence relationship of various technical indicators cannot be reflected in the entire scoring standard formulation, and it is impossible to test whether the logic of subjective judgment is consistent. For example, A is more important than B, and B is more important than C. When the logic is consistent, A needs to be more than C Obviously important; but in the existing scoring standards, the logic cannot be tested, and there may be logic errors that cannot be detected.

Summary of the invention

The purpose of the embodiments of this application is to propose a method, device, computer equipment, and storage medium for data processing of technical indicators, so that the setting of technical indicators is no longer artificially determined, but subjective judgments are digitized, and mathematical models are provided at the same time. Solution, and support the consistency test.

In order to solve the above technical problems, the embodiments of the present application provide a method for data processing of technical indicators, which adopts the following technical solution: according to the demand target, the technical indicators in the scoring standard are determined, and the technical indicators are decomposed according to levels, Establish a hierarchical structure in the database; corresponding to the same technical index in the previous level, each technical index in the next level is compared in pairs in importance, and a data-based judgment matrix is output; the calculated judgment matrix is calculated according to the judgment matrix. The relative weights of the compared technical indicators to the technical indicators of the upper layer, and the weights of the technical indicators of each layer to the target are calculated according to the relative weights; and when the judgment matrix passes the consistency test, according to the technical indicators of each layer and the corresponding The weight calculates the score and stores the score in the database.

In order to solve the above technical problems, the embodiments of the present application also provide a technical indicator data processing device, which adopts the following technical solution: a hierarchical decomposition module is used to determine the technical indicators in the scoring standard according to the needs and objectives, and The technical indicators are decomposed according to levels, and a hierarchical structure is established in the database; the technical indicator digitization module is used to correspond to the same technical indicator in the previous level, and the importance of each technical indicator in the next level is compared in pairs. , Output a digitized judgment matrix; a calculation module, used to calculate the relative weight of the compared technical indicator to the technical indicator of the upper layer according to the judgment matrix, and calculate the weight of the technical indicator of each layer to the target according to the relative weight ; The scoring module is used to calculate the score according to the technical indicators of each level and the corresponding weight when the judgment matrix passes the consistency test, and store the score in the database.

In order to solve the above-mentioned technical problems, the embodiments of the present application also provide a technical index data processing device. The technical index data processing device includes a processor, a memory, and a technical index data processing program stored in the memory. When the technical indicator data processing program is run by the processor, a method for processing technical indicators data is realized, wherein the method for processing technical indicators data includes:

According to the demand target, determine the technical indicators in the scoring standard, and decompose the technical indicators according to levels, and establish a hierarchical structure in the database;

Corresponding to the same technical index in the previous level, the importance of each technical index in the next level is compared in pairs, and a data-based judgment matrix is output;

Calculate the relative weight of the compared technical indicator to the technical indicator of the upper layer according to the judgment matrix, and calculate the weight of the technical indicator of each layer to the target according to the relative weight; and

When the judgment matrix passes the consistency test, the score is calculated according to the technical indicators of each level and the corresponding weight, and the score is stored in the database.

In order to solve the above technical problems, the embodiments of the present application further provide a computer-readable storage medium having a computer program stored on the computer-readable storage medium, and when the computer program is executed by a processor, a method for processing technical indicators data is realized, wherein , The data processing method of the technical indicators includes the following steps:

The setting of indicators in this application is no longer artificially determined. By decomposing the technical indicators according to levels, establishing a hierarchical structure in the database, and outputting a data-based judgment matrix, the technical indicators are converted into data for processing. The logic of the solution supports the judgment of consistency by providing the solution method of the mathematical model, thus greatly reducing the subjective judgment of people.

Description of the drawings

Fig. 1 is a flowchart of an embodiment of a data processing method for technical indicators according to the present application;

Figure 2 is a schematic structural diagram of an embodiment of establishing a hierarchy in a database according to the present application;

FIG. 3 is a schematic structural diagram of an embodiment of the judgment matrix of the criterion layer for the target layer according to the digitization of this application;

FIG. 4 is a schematic structural diagram of an embodiment of a judgment matrix for the functional requirements in the criterion layer according to the digitized index layer of this application;

Fig. 5 is a schematic structural diagram of an embodiment of a judgment matrix for non-functional requirements in the criterion layer in the index layer digitized according to the application;

Fig. 6 is a schematic structural diagram of an embodiment of a judgment matrix implemented for items in the criterion layer according to the digitized index layer of this application;

Fig. 7 is a schematic structural diagram of an embodiment of a data processing device according to the technical indicators of the present application;

Fig. 8 is a schematic structural diagram of an embodiment of a data processing device according to the technical indicators of the present application.

Detailed ways

As shown in Fig. 1, the method for data processing of technical indicators in the embodiment of the present application includes the following steps:

Step 101: Determine the technical indicators in the scoring standard according to the requirements for rapid integration of technical sections, and decompose the technical indicators according to levels, and establish a hierarchical structure in the database.

In the embodiment of this application, the analytic hierarchy process (AHP) is used to decompose the technical indicators determined according to the demand target according to the levels, and the echelon is established in the database, which includes the target level and the criteria from top to bottom. Layer and indicator layer. You can also increase the level as needed.

The Analytic Hierarchy Process (AHP) is to achieve the overall goal according to the nature and requirements of the problem. The problem is broken down into levels and divided into interconnected and orderly levels, such as the target level, the criterion level, the sub-criteria level, and the index level. The structure of the question is from top to bottom, and the relative weight of each element (target) at the same level is determined layer by layer. According to the analytic hierarchy process, complex issues are decomposed, and the components become elements after decomposition, and these elements are divided into several groups according to their attributes to form different levels. Elements of the same level are used as guidelines to dominate certain elements of the next level, and at the same time it is dominated by elements of the upper level.

The levels can be divided into three categories:

(1) The highest level, there is only one element in this level, which is the predetermined goal or ideal result of the problem, so it is also called the target level;

(2) Intermediate level, this level includes the criteria that need to be considered in the intermediate links involved in achieving the goal. This level can also be composed of several levels, that is, there can be criteria and sub-criteria, so this level is also called the criteria level ；

(3) The lowest level. This level includes various measures and decision-making schemes that can be selected to achieve the goal, so it is also called the index level.

In the embodiment of the present application, the elements contained in each level are established respectively, as shown in FIG. 2. The target layer is a scoring standard. The criterion layer includes functional requirements, non-functional requirements and project implementation. The index layer includes product business function integrity, product parameterization degree, product system architecture and internationalization support based on functional requirements, technical advancement, performance and safety based on non-functional requirements, and implementation cases based on project implementation , Personnel qualifications and technology transfer.

Step 102: Corresponding to the same technical indicator in the previous level, the importance of each technical indicator in the next level is respectively compared in pairs to output a data-based judgment matrix.

In the embodiment of this application, the functional requirements, non-functional requirements and project implementation in the criterion layer are compared in pairs relative to the target layer, and the judgment matrix of the digitized criterion layer for the target layer is output, such as Shown in Figure 3.

Compare the importance of the business function integrity, product parameterization degree, product system architecture and internationalization support in the indicator layer with respect to the functional requirements in the standard layer. The output data of the indicator layer is relative to the function in the standard layer. The judgment matrix for sexual requirements is shown in Figure 4.

Compare the importance of the technological advancement, performance and safety in the indicator layer with respect to the non-functional requirements in the criterion layer, and output the judgment matrix of the digitized indicator layer for the non-functional requirements in the criterion layer, as shown in the figure. 5 shown.

Compare the implementation cases, personnel qualifications, and technology transfers in the indicator layer with respect to the project implementation requirements in the criterion layer in terms of importance, and output the judgment matrix of the digitized indicator layer for the project implementation in the criterion layer, as shown in Figure 6. Show.

In Figures 3 to 6, the comparison value between the two factors is given in the judgment matrix. In the embodiment of the present application, setting 0 to 10 indicates that the importance is gradually increased. Of course, other values and importance can also be set. The rules are not restricted here.

In the embodiments of this application, according to the requirements for rapid integration of technical sections, the importance of each element of the same level of technical indicators relative to the importance of each element of the upper level of technical indicators is compared in pairs, according to the pre-determined importance and value Correspondence, which can output a data-based judgment matrix.

Step 103: Calculate the relative weight of the compared element to the technical indicator of the upper layer according to the judgment matrix, and calculate the weight of the technical indicator of each layer to the target according to the relative weight.

In the embodiment of the present application, the rules for calculating the relative weight and the weight are preset. The rule for calculating the relative weight is: calculating the product Mi of each row element Aij in the judgment matrix (the judgment value of the row factor i and the column factor j is Aij);

The rule for calculating the weight is: calculating the n-th root Wi of Mi, and normalizing the vector Wi, and the processed Wi is the weight of each layer element to the target.

Step 104: When the judgment matrix passes the consistency check, a score is calculated according to the technical indicators of each layer and the corresponding weight, and the score is stored in the database.

When A and B are compared in pairs, if A is more important than B and B is more important than C, when the logic is consistent, A needs to be significantly more important than C; and if the comparison value of C is more important than A is calculated, it is logically inconsistent . The calculation of Analytic Hierarchy Process is not simply to get a result, but to get a satisfactory consistent result.

In the embodiments of the present application, the rules for consistency checking are performed on the elements of each layer. The consistency test is judged based on the consistency ratio CR. The consistency judgment based on the consistency ratio CR includes: calculating the consistency index CI; looking up the table to obtain the random consistency index RI; calculating the consistency ratio, CR=CI/RI.

Among them, CI is the consistency index, CI=(λ-n)/(n-1);

In CI

λ is an eigenvalue;

in λ

In the above formula, i=1, 2...n, n is the number of rows; Aij is the judgment value compared between row factor i and column factor j; RI is a random consistency index, RI is obtained by looking up the table, the RI of the third-order matrix = 0.5149, the RI of the fourth-order matrix = 0.8931, the above values are fixed values.

In the embodiment of the present application, when CR<=0.1, it is considered that the consistency check detection is passed, otherwise it is not passed. If the consistency check is passed, the judgment matrix is logically correct, and scores can be made according to the elements of each layer and the corresponding weights, score = element 1 × weight 1 + element 2 × weight 2... + element n × weight n.

Take the judgment matrix of the criterion layer for the target layer shown in Figure 3 as an example, suppose that the functional requirements are as important as the non-functional requirements, with a value of 1; the functional requirements are slightly more important than the project implementation, with a value of 2; Functional requirements are slightly more important than project implementation, with a value of 2; correspondingly, project implementation is not as important as functional requirements, with a value of 0.5; project implementation is not as important as non-functional requirements, with a value of 0.5. When calculating the weight, multiply the value of the corresponding row of the functional requirement, then take the n-th root, and normalize the vector to obtain a composite weight of the functional requirement relative to the target of 0.4. In the same calculation method, the composite weight of the non-functional requirements relative to the target is 0.4, and the composite weight of the project implementation relative to the target is 0.2. When checking the consistency,

And the number of rows is n=3, then CI=(λ-n)/(n-1)=0 of the criterion layer's judgment matrix for the target layer, then CR=CI/RI=0. According to the set CR<=0.1, the consistency check is passed. After the consistency check is passed, the score calculation is performed: score = functional requirements × 0.4 + non-functional requirements × 0.4 + project implementation × 0.2. Store the score in the database.

A person of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing relevant hardware through a computer program. The computer program can be stored in a computer readable storage medium. When executed, it may include the procedures of the above-mentioned method embodiments. Among them, the aforementioned storage medium may be a non-volatile storage medium such as a magnetic disk, an optical disc, a read-only memory (Read-Only Memory, ROM), or a random access memory (Random Access Memory, RAM), etc.

It should be understood that although the various steps in the flowchart of the drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless explicitly stated in this article, the execution of these steps is not strictly limited in order, and they can be executed in other orders. Moreover, at least part of the steps in the flowchart of the drawings may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the order of execution is also It is not necessarily performed sequentially, but may be performed alternately or alternately with at least a part of other steps or sub-steps or stages of other steps.

With further reference to FIG. 7, as an implementation of the above method, this application provides an embodiment of an apparatus 700 for processing technical indicators data, which corresponds to the method embodiment shown in FIG. 1. As shown in FIG. 7, an embodiment of the present application provides a technical index data processing device 700, which includes:

The hierarchical decomposition module 71 is used to determine the technical indicators in the scoring standard according to the needs and goals, and decompose the technical indicators according to levels, and establish a hierarchical structure in the database;

The technical indicator digitization module 72 is used to compare the importance of each technical indicator in the next level corresponding to the same technical indicator in the previous level, and output a digitized judgment matrix;

The calculation module 73 is configured to calculate the relative weight of the compared technical indicator to the technical indicator of the upper layer according to the judgment matrix, and calculate the weight of the technical indicator of each layer to the target according to the relative weight;

The scoring module 74 is used to calculate the score according to the technical indicators and corresponding weights of each level when the judgment matrix passes the consistency test, and store the score in the database.

As shown in FIG. 8, an embodiment of the present application further provides a technical indicator data processing device 800, which includes a processor 81, a memory 82, and a technical indicator data processing program stored in the memory. In the embodiment of the present application, when the technical indicator data processing program is run by the processor, the steps of the aforementioned technical indicator data processing method are realized. The method implemented when the technical indicator data processing program is executed can refer to the various embodiments of the technical indicator data processing method of this application, which will not be repeated here.

The embodiment of the present application also provides a computer-readable storage medium, the computer-readable storage medium stores a technical indicator data processing program, and the storage medium is a volatile storage medium or a non-volatile storage medium. When the technical index data processing program is run by the processor, the steps of realizing the aforementioned technical index data processing method are realized. The method implemented when the technical indicator data processing program is executed can refer to the various embodiments of the technical indicator data processing method of this application, which will not be repeated here.

Claims

A data processing method for technical indicators, which includes the following steps:

According to the demand target, determine the technical indicators in the scoring standard, and decompose the technical indicators according to levels, and establish a hierarchical structure in the database;

Corresponding to the same technical index in the previous level, the importance of each technical index in the next level is compared in pairs, and a data-based judgment matrix is output;

Calculate the relative weight of the compared technical indicator to the technical indicator of the upper layer according to the judgment matrix, and calculate the weight of the technical indicator of each layer to the target according to the relative weight; and

When the judgment matrix passes the consistency test, the score is calculated according to the technical indicators of each level and the corresponding weight, and the score is stored in the database.
The data processing method for technical indicators according to claim 1, wherein the step of decomposing the technical indicators according to levels and establishing a hierarchical structure in the database specifically comprises:

Using the analytic hierarchy process, the technical indicators determined according to the needs and objectives are decomposed according to levels, and the echelon is established in the database, which includes the target level, the criterion level and the index level from top to bottom.
The method for data-based processing of technical indicators according to claim 2, wherein said corresponding to the same technical indicator in the previous level, the technical indicators in the next level are respectively compared for their importance, and the data-based judgment is output The steps of the matrix specifically include:

Each technical indicator in the criterion layer corresponding to the same technical indicator in the target layer is compared in pairs in importance, and the judgment matrix of the digitized criterion layer for the target layer is output;

In the criterion layer, each technical index in the corresponding index layer under the same technical index is compared for importance, and the judgment matrix of the digitized index layer for each technical index in the criterion layer is output respectively.
The data processing method for technical indicators according to claim 3, wherein the target layer includes a scoring standard; the criterion layer corresponds to the functional requirements, non-functional requirements and project implementation of the scoring standard in the target layer; The index layer includes product business function integrity, product parameterization degree, product system architecture and internationalization support corresponding to the functional requirements in the standard layer, technical advancement, performance and safety corresponding to the non-functional requirements in the standard layer, and Corresponding to the implementation cases, personnel qualifications and technology transfer of the project implementation in the standard level;

The steps corresponding to the same technical indicator in the previous level and the importance of each technical indicator in the next level are compared in pairs, and the steps of outputting a digital judgment matrix include:

Compare the functional requirements, non-functional requirements and project implementation importance of the criterion layer corresponding to the scoring criteria in the target layer pairwise, and output the judgment matrix of the digitized criterion layer for the target layer;

Comparing the importance of the index layer corresponding to the functional requirements of the product business function, product parameterization degree, product system architecture, and internationalization support in the standard layer, the output data of the index layer is relative to the standard layer. Judgment matrix for functional requirements;

Compare the importance of the technical advancement, performance and safety of the index layer corresponding to the non-functional requirements in the criterion layer in pairs, and output the judgment matrix of the digitized index layer for the non-functional requirements in the criterion layer;

The importance of the implementation cases, personnel qualifications and technology transfer of the project implementation in the indicator layer corresponding to the criterion layer is compared in pairs, and the judgment matrix of the dataized indicator layer for the project implementation in the criterion layer is output.
The method for processing technical indicators data according to claim 3, wherein the rule for calculating the relative weight is: calculating the product Mi of each row element Aij in the judgment matrix, where Aij is the row factor i and the column factor j The judgment value of the comparison;

The rule for calculating the weight according to the relative weight is: calculating the n-th root Wi of Mi, and normalizing the vector Wi, and the processed Wi is the weight of each layer element to the target.
The data processing method of technical indicators according to claim 5, wherein the consistency check is judged according to the consistency ratio CR, which specifically includes:

Calculate the consistency index CI;

Look up the table to get the random consistency index RI;

Calculate the consistency ratio CR, where CR=CI/RI;

Among them, CI=(λ-n)/(n-1); in CI
λ is the eigenvalue; in λ
n is the number of rows; Aij is the judgment value of comparing row factor i with column factor j.
The method for data processing of technical indicators according to claim 6, wherein when the judgment matrix passes the consistency check, the step of calculating the score according to the technical indicators of each level and the corresponding weight, and storing the score in the database specifically includes :

When the CR is less than the preset value, the consistency check is passed, and the logic of the judgment matrix is correct; the score is calculated according to the technical indicators of each level and the corresponding weight, score=element 1×weight 1+element 2 × weight 2...... + element n × weight n; store the score in the database.
A technical index data processing device, which includes:

The hierarchical decomposition module is used to determine the technical indicators in the scoring standard according to the needs and objectives, and decompose the technical indicators according to the levels, and establish a hierarchical structure in the database;

The technical indicator data module is used to compare the importance of each technical indicator in the next level corresponding to the same technical indicator in the previous level, and output a data-based judgment matrix;

The calculation module is configured to calculate the relative weight of the compared technical indicator to the technical indicator of the upper layer according to the judgment matrix, and calculate the weight of the technical indicator of each layer to the target according to the relative weight;

The scoring module is used to calculate the score according to the technical indicators and corresponding weights of each level when the judgment matrix passes the consistency test, and store the score in the database.
A technical indicator data processing device, wherein the technical indicator data processing device includes a processor, a memory, and a technical indicator data processing program stored in the memory, and the technical indicator data processing program is When the processor is running, a method for data processing of technical indicators is implemented, wherein the method for data processing of technical indicators includes:

According to the demand target, determine the technical indicators in the scoring standard, and decompose the technical indicators according to levels, and establish a hierarchical structure in the database;

Corresponding to the same technical index in the previous level, the importance of each technical index in the next level is compared in pairs, and a data-based judgment matrix is output;

Calculate the relative weight of the compared technical indicator to the technical indicator of the upper layer according to the judgment matrix, and calculate the weight of the technical indicator of each layer to the target according to the relative weight; and

When the judgment matrix passes the consistency test, the score is calculated according to the technical indicators of each level and the corresponding weight, and the score is stored in the database.
The technical indicator data processing equipment according to claim 9, wherein the step of decomposing the technical indicators according to levels and establishing a hierarchical structure in the database specifically comprises:

Using the analytic hierarchy process, the technical indicators determined according to the needs and objectives are decomposed according to levels, and the echelon is established in the database, which includes the target level, the criterion level and the index level from top to bottom.
The technical indicator data processing device according to claim 10, wherein the corresponding technical indicators in the previous level and the technical indicators in the next level are compared in pairs of importance respectively, and the digital judgment is output The steps of the matrix specifically include:

Each technical indicator in the criterion layer corresponding to the same technical indicator in the target layer is compared in pairs in importance, and the judgment matrix of the digitized criterion layer for the target layer is output;

For each technical indicator in the corresponding indicator layer under the same technical indicator in the criterion layer, the importance of the pairwise comparison is performed, and the judgment matrix of the digitized indicator layer for each technical indicator in the criterion layer is output respectively.
The technical indicator data processing equipment according to claim 11, wherein the target layer includes a scoring standard; the criterion layer corresponds to the functional requirements, non-functional requirements and project implementation of the scoring standard in the target layer; The indicator layer includes the product business function integrity, product parameterization degree, product system architecture and internationalization support corresponding to the functional requirements in the standard layer, technical advancement, performance and safety corresponding to the non-functional requirements in the standard layer, and Corresponding to the implementation cases, personnel qualifications and technology transfer of the project implementation in the standard level;

The steps corresponding to the same technical indicator in the previous level and the importance of each technical indicator in the next level are compared in pairs, and the steps of outputting a digital judgment matrix include:

Compare the functional requirements, non-functional requirements and project implementation importance of the criterion layer corresponding to the scoring criteria in the target layer pairwise, and output the judgment matrix of the digitized criterion layer for the target layer;

Comparing the importance of the index layer corresponding to the functional requirements of the product business function, product parameterization degree, product system architecture, and internationalization support in the standard layer, the output data of the index layer is relative to the standard layer. Judgment matrix for functional requirements;

Compare the importance of the technical advancement, performance and safety of the index layer corresponding to the non-functional requirements in the criterion layer in pairs, and output the judgment matrix of the digitized index layer for the non-functional requirements in the criterion layer;

The importance of the implementation cases, personnel qualifications and technology transfer of the project implementation in the indicator layer corresponding to the criterion layer is compared in pairs, and the judgment matrix of the dataized indicator layer for the project implementation in the criterion layer is output.
The technical index data processing device according to claim 11, wherein the rule for calculating the relative weight is: calculating the product Mi of each row element Aij in the judgment matrix, where Aij is the row factor i and the column factor j The judgment value of the comparison;

The rule for calculating the weight according to the relative weight is: calculating the n-th root Wi of Mi, and normalizing the vector Wi, and the processed Wi is the weight of each layer element to the target.
The technical indicator data processing equipment according to claim 13, wherein the consistency check is judged based on the consistency ratio CR, which specifically includes:

Calculate the consistency index CI;

Look up the table to get the random consistency index RI;

Calculate the consistency ratio CR, where CR=CI/RI;

Among them, CI=(λ-n)/(n-1); in CI
λ is the eigenvalue; in λ
n is the number of rows; Aij is the judgment value of comparing row factor i with column factor j.
The technical indicator data processing equipment according to claim 14, wherein when the judgment matrix passes the consistency check, the step of calculating the score according to the technical indicators of each level and the corresponding weight, and storing the score in the database specifically includes :

When the CR is less than the preset value, the consistency check is passed, and the logic of the judgment matrix is correct; the score is calculated according to the technical indicators of each level and the corresponding weight, score=element 1×weight 1+element 2 × weight 2...... + element n × weight n; store the score in the database.
A computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, a method for data processing of technical indicators is realized, wherein the method for data processing of technical indicators includes The following steps:

According to the demand target, determine the technical indicators in the scoring standard, and decompose the technical indicators according to levels, and establish a hierarchical structure in the database;

Corresponding to the same technical index in the previous level, the importance of each technical index in the next level is compared in pairs, and a data-based judgment matrix is output;

Calculate the relative weight of the compared technical indicator to the technical indicator of the upper layer according to the judgment matrix, and calculate the weight of the technical indicator of each layer to the target according to the relative weight; and

When the judgment matrix passes the consistency test, the score is calculated according to the technical indicators of each level and the corresponding weight, and the score is stored in the database.
16. The computer-readable storage medium according to claim 16, wherein the step of decomposing the technical indicators according to levels and establishing a hierarchical structure in the database specifically comprises:

Using the analytic hierarchy process, the technical indicators determined according to the needs and objectives are decomposed according to levels, and the echelon is established in the database, which includes the target level, the criterion level and the index level from top to bottom.
17. The computer-readable storage medium according to claim 17, wherein said corresponding to the same technical indicator in the previous level, the technical indicators in the next level are respectively compared for their importance to output a data-based judgment matrix The specific steps include:

Each technical indicator in the criterion layer corresponding to the same technical indicator in the target layer is compared in pairs in importance, and the judgment matrix of the digitized criterion layer for the target layer is output;

For each technical indicator in the corresponding indicator layer under the same technical indicator in the criterion layer, the importance of the pairwise comparison is performed, and the judgment matrix of the digitized indicator layer for each technical indicator in the criterion layer is output respectively.
18. The computer-readable storage medium according to claim 18, wherein the target layer includes scoring standards; the criterion layer corresponds to functional requirements, non-functional requirements, and project implementation of the scoring standards in the target layer; and the indicators The layer includes product business function integrity, product parameterization degree, product system architecture and internationalization support corresponding to the functional requirements in the standard layer, technical advancement, performance and safety corresponding to the non-functional requirements in the standard layer, and corresponding Implementation cases, personnel qualifications and technology transfer of project implementation in the standard level;

The steps corresponding to the same technical indicator in the previous level and the importance of each technical indicator in the next level are compared in pairs, and the steps of outputting a digital judgment matrix include:

Compare the functional requirements, non-functional requirements and project implementation importance of the criterion layer corresponding to the scoring criteria in the target layer pairwise, and output the judgment matrix of the digitized criterion layer for the target layer;

Comparing the importance of the index layer corresponding to the functional requirements of the product business function, product parameterization degree, product system architecture, and internationalization support in the standard layer, the output data of the index layer is relative to the standard layer. Judgment matrix for functional requirements;

Compare the importance of the technical advancement, performance and safety of the index layer corresponding to the non-functional requirements in the criterion layer in pairs, and output the judgment matrix of the digitized index layer for the non-functional requirements in the criterion layer;

The importance of the implementation cases, personnel qualifications and technology transfer of the project implementation in the indicator layer corresponding to the criterion layer is compared in pairs, and the judgment matrix of the dataized indicator layer for the project implementation in the criterion layer is output.
The computer-readable storage medium according to claim 18, wherein the rule for calculating the relative weight is: calculating the product Mi of each row element Aij in the judgment matrix, where Aij is the comparison between the row factor i and the column factor j Judgment value;

The rule for calculating the weight according to the relative weight is: calculating the n-th root Wi of Mi, and normalizing the vector Wi, and the processed Wi is the weight of each layer element to the target.