CN112907026A - Comprehensive evaluation method based on editable mesh index system - Google Patents
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Abstract
The invention discloses a comprehensive evaluation method based on an editable mesh index system, which comprises the following steps: obtaining a problem to be evaluated; setting indexes to be evaluated according to the problems to be evaluated, determining the incidence relation among the indexes to be evaluated, and generating an editable mesh index system; constructing an aggregation calculation process based on an aggregation calculation process generation method according to an editable mesh index system; setting the weight and calculation parameters of the indexes to be evaluated in an editable mesh index system; editing specified input data and a mapping relation between the input data and an editable mesh index system; editing a data preprocessing process on the input data; setting actual evaluation data as input data, performing comprehensive evaluation calculation based on an editable mesh index system, and displaying an evaluation result. The method is convenient for updating and maintaining the index system and the calculation process, can measure the correlation degree between the associated indexes, and well reflects the relationship between the indexes.
Description
Technical Field
The invention relates to the technical field of computer evaluation, in particular to a comprehensive evaluation method based on an editable mesh index system.
Background
At present, various industries have a great number of problems, and accurate assessment and decision making are required. With the popularization of computers, more and more convenient basic data collection and storage scheme design enables accurate decision making, and the accurate decision making of things depends on comprehensive evaluation of relevant indexes. A large part of the existing comprehensive evaluation method and evaluation system is only suitable for targeted application and field, and does not support the modification and construction of an index system and a calculation process. In the evaluation process, the evaluation is carried out according to the data provided by the user, and even when the index system and the aggregation process are changed, the user cannot carry out related improvement by himself or herself and only depends on the updating of software.
In the prior art, only development and construction support for a tree index system is provided. Namely, indexes in the index system are tree-shaped hierarchical relations, one index depends on a plurality of child indexes, and each index can only provide data support for a parent node of the index. As shown in FIG. 1, the result of the top level index depends on the results of its subordinate three secondary indexes, and the result of each secondary index depends on the result of its respective sub-index. During calculation, the values of all the three-level indexes are calculated firstly, and then the values are gradually aggregated to the secondary indexes till the top-level indexes.
The prior art has the following technical problems: 1. the method has a fixed index system and a fixed aggregation process, is not beneficial to updating and maintaining the index system and the calculation process, and cannot be maintained through software when evaluation data, the index system, the aggregation process and the like are changed, and only depends on program upgrading; 2. for a comprehensive evaluation system only having a tree-shaped index system editing function, the characteristics of correlation among indexes are not completely met, and the evaluation of a plurality of indexes cannot be supported under the condition that one index is depended on at the same time; 3. the construction of an index system can be carried out only depending on experience, and the correlation degree between the correlation indexes cannot be measured; 4. the construction of the index system and the aggregation process requires a large amount of manual work, no related data and tool support exists, and the constructed index system and the aggregation process cannot well reflect the relationship between indexes.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the art described above. Therefore, the invention aims to provide a comprehensive evaluation method based on an editable mesh index system, which is convenient for updating and maintaining the index system and the calculation process, can measure the correlation degree between the associated indexes, and well reflects the relationship between the indexes.
In order to achieve the above object, an embodiment of the present invention provides a comprehensive evaluation method based on an editable mesh index system, including:
obtaining a problem to be evaluated;
setting indexes to be evaluated according to the problems to be evaluated, determining the incidence relation among the indexes to be evaluated, and generating an editable mesh index system;
constructing an aggregation calculation process based on an aggregation calculation process generation method according to an editable mesh index system;
setting the weight and calculation parameters of the indexes to be evaluated in an editable mesh index system;
editing specified input data and a mapping relation between the input data and an editable mesh index system;
editing a data preprocessing process on the input data;
setting actual evaluation data as input data, performing comprehensive evaluation calculation based on an editable mesh index system, and displaying an evaluation result.
According to some embodiments of the present invention, the determining the association relationship between the indicators to be evaluated and generating an editable mesh indicator system includes:
determining an index to be evaluated and an attribute relation between the indexes to be evaluated, and setting sample data for the indexes to be evaluated;
calculating a correlation coefficient between indexes to be evaluated according to a preset relation between the sample data and the sample data;
and sorting the correlation coefficients among the indexes to be evaluated, generating the incidence relation among the indexes to be evaluated according to the magnitude of the correlation coefficients, and generating an editable mesh index system.
According to some embodiments of the invention, before generating the editable mesh index system, further comprising: and analyzing the correlation coefficient and the incidence relation between the indexes to be evaluated by adopting a structural equation modeling method.
According to some embodiments of the present invention, the analyzing the correlation coefficient and the correlation relationship between the indexes to be evaluated by using the structural equation modeling method includes:
establishing a model according to the indexes to be evaluated preliminarily established and provided by the user and the attribute relation between the indexes to be evaluated;
fitting the established model by using a structural equation modeling method;
calculating a fitting coefficient of each index to be evaluated; the fitting coefficient comprises at least one of a chi-square value, a fitting index, a relative fitting index, a normalized residual error and an approximate root mean square error;
and displaying and analyzing the fitting coefficient by a visualization method.
According to some embodiments of the invention, the building an aggregate computing process based on an aggregate computing process generation method according to the editable mesh index system comprises:
selecting a target index in an editable mesh index system as an output port of the aggregation calculation process;
determining one or more indexes to be evaluated, which provide support for the target indexes, as input ports of an aggregation calculation process according to the incidence relation of the target indexes;
and editing the flow direction of the input data among operators by adding operators and setting operator attributes according to the input port and the output port to construct an aggregation calculation process.
According to some embodiments of the present invention, setting actual evaluation data as input data for a comprehensive evaluation calculation based on an editable mesh index system includes:
s11, constructing an editable mesh index system S;
S＝<V,L>
wherein, V is an index set to be evaluated; l is an incidence relation set among indexes to be evaluated;
s12, calculating the degree of entry of each evaluation node in the index set to be evaluated;
s13, adding the evaluation nodes with the degree of income 0 into the calculation queue in sequence, deleting the evaluation nodes with the degree of income 0 from the index set to be evaluated, and deleting the incidence relation taking the index set to be evaluated as the initial evaluation node from the incidence relation set among the indexes to be evaluated;
s14, repeating the step S12 until all the evaluation nodes are added into the calculation queue;
s15, calculating the aggregation calculation process corresponding to each index to be evaluated one by one, and storing the calculation result;
and S16, processing and evaluating the calculation result by applying a pre-defined scoring method, a reasonable interval and an evaluation rule to generate a final evaluation result.
According to some embodiments of the invention, the aggregate calculation process generation method comprises at least one of a ring ratio coefficient method, a weighted average method, and a comprehensive fuzzy evaluation method.
According to some embodiments of the invention, the index to be evaluated is set as a new index or a usable index is selected from an existing index list;
the indexes to be evaluated comprise index names, index descriptions, scoring methods, reasonable intervals and evaluation rules.
In one embodiment, before applying a pre-defined scoring method, a reasonable interval, and an evaluation rule to process and evaluate the calculation result and generate a final evaluation result, the method includes:
acquiring calling information of each evaluation node in an index set to be evaluated;
correcting the calculation sequence of each index to be evaluated according to the calling information to obtain a corrected calculation sequence;
acquiring first attribute data of a plurality of calculation results;
according to the modified calculation sequence and the consumption of a plurality of calculation results of the first attribute data according to a preset data buffer queue, converting the first attribute data into second attribute data in a preset format, extracting time sequence data in the second attribute data and sequencing;
performing feature extraction on the sequenced time sequence data to acquire dimension data of the time sequence data;
establishing a corresponding dimension coordinate system according to the dimension data;
acquiring a display instruction of a user;
and displaying a plurality of calculation results in a dimensional coordinate system according to the display instruction.
In an embodiment, after determining the association relationship between the indexes to be evaluated, the method further includes calculating the reliability of the association relationship, and marking the association relationship with the reliability less than the preset reliability;
the calculating the credibility of the association relationship comprises the following steps:
selecting an index to be evaluated as a confidence index, and acquiring an associated index having an associated relation with the confidence index according to the associated relation of the confidence index;
calculating the credibility K of the confidence index in the attribute set A1：
Wherein, baIs a confidence index; f1Is a membership function of the confidence index on the attribute set A; u is the discourse domain where the confidence index and the correlation index are located; n is the number of all indexes on the attribute set A; bxIs the x index on the attribute set A; t (b)a，bx) Similarity between the confidence index and the x index on the attribute set A is obtained;
calculating the credibility K of the correlation index in the relative attribute set (R-A)2：
Wherein, bcIs a correlation index; f2Is A membership function of the correlation index on A relative attribute set (R-A); m is a relative attributeThe number of all indices on set (R-A); byIs the y index on the relative attribute set (R-A); t (b)c，by) Similarity of the associated index and the y index on the relative attribute set (R-A) is taken as A similarity; r is the total attribute set;
credibility K in attribute set A according to confidence index1And the reliability K of the associated index in the relative attribute set (R-A)2Calculating the reliability K of the association relation3：
And when the credibility of the association relation is less than the preset credibility, marking the association relation.
Has the advantages that:
1. the editing, constructing and index calculating processes of the mesh index system are provided, and the evaluation application which is more practical can be better fitted.
2. The method and the tool for calculating the correlation coefficient between the indexes are provided, and better data reference can be provided for a user to construct an index system.
3. The method for automatically constructing the index system is provided, the operation of a user is simplified, and a favorable tool is provided for the user to quickly and reasonably construct the index system.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of a prior art tree index system;
FIG. 2 is a flow diagram of a comprehensive evaluation method based on editable mesh index systems according to one embodiment of the invention;
FIG. 3 is a schematic diagram of an editable mesh index system according to an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
A comprehensive evaluation method based on an editable mesh index system, which is proposed by the embodiment of the present invention, is described below with reference to fig. 2 to 3, and can be used for analyzing, calculating, measuring and comparing various things, such as various schemes, plans, industrial processes, scientific experiments, product quality and performance, asset value, and the like, to form valuable information for result inspection, decision support, and the like. The invention can be applied to various evaluation services with determined evaluation data and evaluation flows in various industries.
As shown in fig. 2, an embodiment of the present invention provides a comprehensive evaluation method based on an editable mesh index system, including steps S1-S7:
s1, obtaining the problem to be evaluated;
s2, setting indexes to be evaluated according to the problems to be evaluated, determining the incidence relation among the indexes to be evaluated, and generating an editable mesh index system;
s3, constructing an aggregation calculation process based on an aggregation calculation process generation method according to the editable mesh index system;
s4, setting the weight and calculation parameters of the index to be evaluated in the editable mesh index system;
s5, editing the designated input data and the mapping relation between the input data and the editable mesh index system;
s6, editing the data preprocessing process of the input data;
and S7, setting actual evaluation data as input data, performing comprehensive evaluation calculation based on an editable mesh index system, and displaying an evaluation result.
The working principle of the technical scheme is as follows: evaluation: i.e., the process of evaluating the measures, analyzing against known solutions, processes, or results, and computing metrics to support decision-making. And (3) comprehensive evaluation: evaluation can be divided into a number of aspects. Comprehensive evaluation refers to the evaluation of things in multiple levels and multiple angles. Indexes are as follows: each description of the characteristics of the object to be evaluated is called an index. Index system: a set of indices and relationships for evaluating a certain event. Mesh index system: the relation between indexes is an index system of a network structure. The invention also provides the support of a mesh index system and related support nodes on the basis of having a flexible tree index system and an aggregation process editing function. Before comprehensive evaluation, the problem to be evaluated is obtained, specifically, the process of analyzing the problem and determining what needs to be evaluated and how to evaluate is performed by the user. Setting indexes to be evaluated according to the problems to be evaluated, determining the incidence relation among the indexes to be evaluated, and generating an editable mesh index system; as shown in fig. 3, unlike the tree-shaped index system with only hierarchical and branch aggregation, the mesh-shaped index system is a forest with topological relation, and can simultaneously support multiple final indexes. Such as index 8, index 11, index 12, and index 13 are final indexes. The result value of one index can provide aggregation support for multiple indexes simultaneously. For example, index 1 may provide support for both index 2 and index 12. Index 2 may provide support for both index 3 and index 5. While the software allows the presence of isolated indicators. An isolated indicator (e.g., indicator 13) can result from merely processing the input data for that indicator. Constructing an aggregation calculation process based on an aggregation calculation process generation method according to an editable mesh index system; the incidence relation between the indexes to be evaluated is expressed through a specific aggregation calculation process. The aggregation calculation process is defined as a group of operators and the ordered combination of attribute configuration and data circulation relation among the operators. In one embodiment, the generation of the aggregation calculation process is automatically realized by an aggregation calculation process generation method, and the method is suitable for the generation of a common simple aggregation calculation process. In addition, the user may manually edit the aggregate calculation process according to an editing tool provided in the integrated evaluation system. Setting the weight and calculation parameters of the indexes to be evaluated in an editable mesh index system; the setting of the weights and calculation parameters is performed manually, or may be automatically set using a weight generator provided by the system. Editing the organization form of the specified input data and the mapping relation between the input data field and the input index in the editable mesh index system. Editing the data preprocessing process of the input data, defining the preprocessing process of the input data according to a data preprocessing tool provided by the system, and completing the data preprocessing through operators and editing of data streams, similar to the editing and aggregating calculation process. The user can set actual evaluation data as input data, the actual evaluation data is in accordance with the data form set in S5, comprehensive evaluation calculation is performed based on the editable mesh index system, and the evaluation result is displayed.
The beneficial effects of the above technical scheme are that: the editing, constructing and index calculating processes of the mesh index system are provided, and the evaluation application which is more practical can be better fitted. The method and the tool for calculating the correlation coefficient between the indexes are provided, and better data reference can be provided for a user to construct an index system. According to the correlation among indexes to be evaluated, the method can be directly used for building an evaluation model, and can also be used as a basis and a reference for building an index system by a user, so that the user can conveniently build the index system, the operation of the user is simplified, and a favorable tool is provided for the user to quickly and reasonably build the index system.
In one embodiment, the system supports comparison and analysis of results of multiple evaluations for the evaluation results, and shows differences of the evaluation results between evaluation schemes or evaluation data of different batches in the form of a graph, so as to analyze variation trends of indexes or advantages and disadvantages of the evaluation schemes.
According to some embodiments of the present invention, the determining the association relationship between the indicators to be evaluated and generating an editable mesh indicator system includes:
determining an index to be evaluated and an attribute relation between the indexes to be evaluated, and setting sample data for the indexes to be evaluated;
calculating a correlation coefficient between indexes to be evaluated according to a preset relation between the sample data and the sample data;
and sorting the correlation coefficients among the indexes to be evaluated, generating the incidence relation among the indexes to be evaluated according to the magnitude of the correlation coefficients, and generating an editable mesh index system.
The working principle of the technical scheme is as follows: determining indexes to be evaluated, acquiring attributes of the indexes to be evaluated, determining attribute relations among the indexes to be evaluated according to an attribute correlation principle, and setting sample data for the indexes to be evaluated; calculating a correlation coefficient between indexes to be evaluated according to a preset relation between the sample data and the sample data; and sorting the correlation coefficients among the indexes to be evaluated, generating the incidence relation among the indexes to be evaluated according to the magnitude of the correlation coefficients, and automatically generating a recommended index system according to the incidence relation. The user can manually adjust the index system according to the requirement and the condition of executing the calculation result, and can also directly use the recommended index system for calculation. The user can repeat the above processes as required until a satisfactory index system is obtained, i.e. an editable mesh index system is generated. In one implementation, the user edits the association between the indicators manually.
The beneficial effects of the above technical scheme are that: the method and the tool for calculating the correlation coefficient between the indexes are provided, and better data reference can be provided for a user to construct an index system.
According to some embodiments of the invention, before generating the editable mesh index system, further comprising: and analyzing the correlation coefficient and the incidence relation between the indexes to be evaluated by adopting a structural equation modeling method.
The working principle and the beneficial effects of the technical scheme are as follows: structural Equation Modeling (SEM for short) is a statistical data analysis tool formed by comprehensively using multivariate regression analysis, path analysis and confirmation type factor analysis methods, is a statistical method for analyzing variable relationships based on a covariance matrix of variables, is also called covariance Structural analysis, and can analyze and process measurement errors and also analyze Structural relationships among latent variables. The correlation coefficient and the incidence relation between the indexes to be evaluated are analyzed by adopting a structural equation modeling method, so that the accuracy of the correlation coefficient and the relation is ensured, an accurate mesh index system is generated, and the accuracy of an evaluation result is favorably output.
According to some embodiments of the present invention, the analyzing the correlation coefficient and the correlation relationship between the indexes to be evaluated by using the structural equation modeling method includes:
establishing a model according to the indexes to be evaluated preliminarily established and provided by the user and the attribute relation between the indexes to be evaluated;
fitting the established model by using a structural equation modeling method;
calculating a fitting coefficient of each index to be evaluated; the fitting coefficient comprises at least one of a chi-square value, a fitting index, a relative fitting index, a normalized residual error and an approximate root mean square error;
and displaying and analyzing the fitting coefficient by a visualization method.
The working principle of the technical scheme is as follows: establishing a model according to the indexes to be evaluated preliminarily established and provided by the user and the attribute relation between the indexes to be evaluated; fitting the established model by using a structural equation modeling method; calculating a fitting coefficient of each index to be evaluated; the fitting coefficient comprises at least one of a chi-square value, a fitting index, a relative fitting index, a normalized residual error and an approximate root mean square error; and displaying and analyzing the fitting coefficient by a visualization method.
The beneficial effects of the above technical scheme are that: and analyzing the correlation between the indexes to be evaluated, and obtaining the mutual causal relationship between the indexes to be evaluated, the correlation degree of the relationship between the indexes to be evaluated and the hidden relationship between the indexes to be evaluated through the analysis. The user can establish a more accurate evaluation model according to the analysis result, and the user can clearly know the relevant fitting coefficient and adjust and monitor the fitting coefficient.
According to some embodiments of the invention, the building an aggregate computing process based on an aggregate computing process generation method according to the editable mesh index system comprises:
selecting a target index in an editable mesh index system as an output port of the aggregation calculation process;
determining one or more indexes to be evaluated, which provide support for the target indexes, as input ports of an aggregation calculation process according to the incidence relation of the target indexes;
and editing the flow direction of the input data among operators by adding operators and setting operator attributes according to the input port and the output port to construct an aggregation calculation process.
The working principle and the beneficial effects of the technical scheme are as follows: illustratively, an index A is selected as a target index, the index A is used as an output port, an index which is related to and supports the index A, namely an index B, is determined according to the incidence relation of the index A, the index B is used as an input port of the aggregation calculation process, and the aggregation calculation process is constructed by adding operators, setting operator attributes, editing the flow direction of input data among operator ports and the like. The accuracy of the aggregation calculation process is guaranteed, meanwhile, the calculation complexity is reduced, the calculation amount is reduced, the quick response and the quick construction are improved, the waiting for too long time is avoided, and the user experience is improved.
According to some embodiments of the present invention, setting actual evaluation data as input data for a comprehensive evaluation calculation based on an editable mesh index system includes:
s11, constructing an editable mesh index system S;
S＝<V,L>
wherein, V is an index set to be evaluated; l is an incidence relation set among indexes to be evaluated;
s12, calculating the degree of entry of each evaluation node in the index set to be evaluated;
s13, adding the evaluation nodes with the degree of income 0 into the calculation queue in sequence, deleting the evaluation nodes with the degree of income 0 from the index set to be evaluated, and deleting the incidence relation taking the index set to be evaluated as the initial evaluation node from the incidence relation set among the indexes to be evaluated;
s14, repeating the step S12 until all the evaluation nodes are added into the calculation queue;
s15, calculating the aggregation calculation process corresponding to each index to be evaluated one by one, and storing the calculation result;
and S16, processing and evaluating the calculation result by applying a pre-defined scoring method, a reasonable interval and an evaluation rule to generate a final evaluation result.
The working principle of the technical scheme is as follows: the mesh index system is represented as a set of index nodes with attributes and an edge set that describes the relationships between the nodes. Namely: s ═<V,L>Wherein S is a mesh index system; v is an index set to be evaluated contained in a mesh index system: v ═ V1，V2，Vi……Vj……Vn}; l is an incidence relation set among indexes to be evaluated: l ═ Lij}。LijAs an index V to be evaluatediTo VjThe association relationship between them. Calculating the degree of entry of each evaluation node in the index set to be evaluated; adding the evaluation nodes with the degree of 0 into the calculation queue in sequence, deleting the evaluation nodes with the degree of 0 from the index set to be evaluated, and deleting the incidence relation taking the index set to be evaluated as the initial evaluation node from the incidence relation set among the indexes to be evaluated; repeatedly executing the step S12 until all the evaluation nodes are added into the calculation queue; calculating the aggregation calculation process corresponding to each index to be evaluated one by one, and storing the calculation result; and processing and evaluating the calculation result by applying a pre-defined scoring method, a reasonable interval and an evaluation rule to generate a final evaluation result.
The beneficial effects of the above technical scheme are that: determining a calculation sequence of an aggregation calculation process according to the incidence relation among indexes to be evaluated, constructing an editable mesh index system, sequentially adding the evaluation nodes into a calculation queue according to the degree of entry of each evaluation node in an index set to be evaluated, determining the calculation sequence, ensuring the logic and accuracy of calculation, avoiding calculation errors, deleting the evaluation nodes with the degree of entry of 0 from the index set to be evaluated after the evaluation nodes with the degree of entry of 0 are sequentially added into the calculation queue, deleting the evaluation nodes with the degree of entry of 0 from the index set to be evaluated, deleting the incidence relation taking the index set to be evaluated as the initial evaluation node from the incidence relation set among the indexes to be evaluated, releasing a system memory, and ensuring the accuracy and quick response of calculation.
According to some embodiments of the invention, the aggregate calculation process generation method comprises at least one of a ring ratio coefficient method, a weighted average method, and a comprehensive fuzzy evaluation method.
According to some embodiments of the invention, the index to be evaluated is set as a new index or a usable index is selected from an existing index list;
the indexes to be evaluated comprise index names, index descriptions, scoring methods, reasonable intervals and evaluation rules.
In one embodiment, before applying a pre-defined scoring method, a reasonable interval, and an evaluation rule to process and evaluate the calculation result and generate a final evaluation result, the method includes:
acquiring calling information of each evaluation node in an index set to be evaluated;
correcting the calculation sequence of each index to be evaluated according to the calling information to obtain a corrected calculation sequence;
acquiring first attribute data of a plurality of calculation results;
according to the modified calculation sequence and the consumption of a plurality of calculation results of the first attribute data according to a preset data buffer queue, converting the first attribute data into second attribute data in a preset format, extracting time sequence data in the second attribute data and sequencing;
performing feature extraction on the sequenced time sequence data to acquire dimension data of the time sequence data;
establishing a corresponding dimension coordinate system according to the dimension data;
acquiring a display instruction of a user;
and displaying a plurality of calculation results in a dimensional coordinate system according to the display instruction.
The working principle and the beneficial effects of the technical scheme are as follows: before the calculation results are processed and evaluated by applying the pre-defined scoring method, the reasonable interval and the evaluation rule to generate the final evaluation result, the obtained calculation results are displayed according to the user requirements, so that the user can check the calculation results conveniently, and the query efficiency is more efficient. Acquiring calling information of each evaluation node in an index set to be evaluated; correcting the calculation sequence of each index to be evaluated according to the calling information to obtain a corrected calculation sequence; the error of the sequence determined according to the degree of entry is eliminated, so that the obtained calculation sequence is more accurate, and accurate calculation is facilitated. Acquiring first attribute data of a plurality of calculation results; the first attribute data includes time data. According to the modified calculation sequence and the consumption of a plurality of calculation results of the first attribute data according to a preset data buffer queue, converting the first attribute data into second attribute data in a preset format, extracting time sequence data in the second attribute data and sequencing; and the incidence relation among a plurality of calculation results is accurately obtained, and the accuracy is conveniently improved when the comprehensive calculation evaluation is calculated. Performing feature extraction on the sequenced time sequence data to acquire dimension data of the time sequence data; establishing a corresponding dimension coordinate system according to the dimension data; acquiring a display instruction of a user; and displaying a plurality of calculation results in a dimensional coordinate system according to the display instruction. The calculation results are accurately displayed in a multi-dimensional mode according to the dimension data of the time sequence data, so that a user can clearly know the time sequence and the dimension information of the calculation results, and the query rate is improved.
In an embodiment, after determining the association relationship between the indexes to be evaluated, the method further includes calculating the reliability of the association relationship, and marking the association relationship with the reliability less than the preset reliability;
the calculating the credibility of the association relationship comprises the following steps:
selecting an index to be evaluated as a confidence index, and acquiring an associated index having an associated relation with the confidence index according to the associated relation of the confidence index;
calculating the credibility K of the confidence index in the attribute set A1：
Wherein, baIs a confidence index; f1Is a membership function of the confidence index on the attribute set A; u is the discourse domain where the confidence index and the correlation index are located; n is the number of all indexes on the attribute set A; bxIs the x index on the attribute set A; t (b)a，bx) Similarity between the confidence index and the x index on the attribute set A is obtained;
calculating the credibility K of the correlation index in the relative attribute set (R-A)2：
Wherein, bcIs a correlation index; f2Is A membership function of the correlation index on A relative attribute set (R-A); m is the number of all indexes on the relative attribute set (R-A); byIs the y index on the relative attribute set (R-A); t (b)c，by) Similarity of the associated index and the y index on the relative attribute set (R-A) is taken as A similarity; r is the total attribute set;
credibility K in attribute set A according to confidence index1And the reliability K of the associated index in the relative attribute set (R-A)2Calculating the reliability K of the association relation3：
And when the credibility of the association relation is less than the preset credibility, marking the association relation.
The working principle and the beneficial effects of the technical scheme are as follows: after determining the incidence relation among the indexes to be evaluated, calculating the reliability of the incidence relation, and marking the incidence relation with the reliability smaller than the preset reliability; the method is convenient for more accurate monitoring, and is also beneficial to removing or disconnecting the incidence relation with the credibility less than the preset credibility, thereby ensuring the accuracy of relation determination and further ensuring the accuracy of aggregate calculation. Selecting an index to be evaluated as a confidence index, and acquiring an associated index having an associated relation with the confidence index according to the associated relation of the confidence index; and calculating the credibility of the confidence index in the attribute set A and the credibility of the associated index in the relative attribute set (R-A), and further accurately calculating the credibility of the association relation between the confidence index and the associated index.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A comprehensive evaluation method based on an editable mesh index system is characterized by comprising the following steps:
obtaining a problem to be evaluated;
setting indexes to be evaluated according to the problems to be evaluated, determining the incidence relation among the indexes to be evaluated, and generating an editable mesh index system;
constructing an aggregation calculation process based on an aggregation calculation process generation method according to an editable mesh index system;
setting the weight and calculation parameters of the indexes to be evaluated in an editable mesh index system;
editing specified input data and a mapping relation between the input data and an editable mesh index system;
editing a data preprocessing process on the input data;
setting actual evaluation data as input data, performing comprehensive evaluation calculation based on an editable mesh index system, and displaying an evaluation result.
2. The comprehensive evaluation method based on editable mesh index system according to claim 1, wherein the determining the incidence relation between the indexes to be evaluated to generate the editable mesh index system includes:
determining an index to be evaluated and an attribute relation between the indexes to be evaluated, and setting sample data for the indexes to be evaluated;
calculating a correlation coefficient between indexes to be evaluated according to a preset relation between the sample data and the sample data;
and sorting the correlation coefficients among the indexes to be evaluated, generating the incidence relation among the indexes to be evaluated according to the magnitude of the correlation coefficients, and generating an editable mesh index system.
3. The editable mesh index system-based comprehensive evaluation method according to claim 2, further comprising, before generating the editable mesh index system: and analyzing the correlation coefficient and the incidence relation between the indexes to be evaluated by adopting a structural equation modeling method.
4. The comprehensive evaluation method based on editable mesh index system according to claim 3, wherein the method of modeling by using structural equations is used for analyzing the correlation coefficient and the incidence relation between the indexes to be evaluated, and the method includes:
establishing a model according to the indexes to be evaluated preliminarily established and provided by the user and the attribute relation between the indexes to be evaluated;
fitting the established model by using a structural equation modeling method;
calculating a fitting coefficient of each index to be evaluated; the fitting coefficient comprises at least one of a chi-square value, a fitting index, a relative fitting index, a normalized residual error and an approximate root mean square error;
and displaying and analyzing the fitting coefficient by a visualization method.
5. The comprehensive evaluation method based on editable mesh index system according to claim 1, wherein the building of the aggregation calculation process based on the aggregation calculation process generation method according to the editable mesh index system comprises:
selecting a target index in an editable mesh index system as an output port of the aggregation calculation process;
determining one or more indexes to be evaluated, which provide support for the target indexes, as input ports of an aggregation calculation process according to the incidence relation of the target indexes;
and editing the flow direction of the input data among operators by adding operators and setting operator attributes according to the input port and the output port to construct an aggregation calculation process.
6. The editable mesh index system-based comprehensive evaluation method according to claim 1, wherein setting actual evaluation data as input data to perform comprehensive evaluation calculation based on the editable mesh index system includes:
s11, constructing an editable mesh index system S;
S＝<V,L>
wherein, V is an index set to be evaluated; l is an incidence relation set among indexes to be evaluated;
s12, calculating the degree of entry of each evaluation node in the index set to be evaluated;
s13, adding the evaluation nodes with the degree of income 0 into the calculation queue in sequence, deleting the evaluation nodes with the degree of income 0 from the index set to be evaluated, and deleting the incidence relation taking the index set to be evaluated as the initial evaluation node from the incidence relation set among the indexes to be evaluated;
s14, repeating the step S12 until all the evaluation nodes are added into the calculation queue;
s15, calculating the aggregation calculation process corresponding to each index to be evaluated one by one, and storing the calculation result;
and S16, processing and evaluating the calculation result by applying a pre-defined scoring method, a reasonable interval and an evaluation rule to generate a final evaluation result.
7. The editable mesh index system-based comprehensive evaluation method according to claim 1, wherein the aggregation calculation process generation method includes at least one of a ring ratio coefficient method, a weighted average method and a comprehensive fuzzy evaluation method.
8. The comprehensive evaluation method based on the editable mesh index system according to claim 1, wherein the index to be evaluated is set as a new index or a usable index is selected from an existing index list;
the indexes to be evaluated comprise index names, index descriptions, scoring methods, reasonable intervals and evaluation rules.
9. The comprehensive evaluation method based on editable mesh index system according to claim 6, before applying the pre-defined scoring method, reasonable interval and evaluation rule to process and evaluate the calculation result and generate the final evaluation result, the method comprises:
acquiring calling information of each evaluation node in an index set to be evaluated;
correcting the calculation sequence of each index to be evaluated according to the calling information to obtain a corrected calculation sequence;
acquiring first attribute data of a plurality of calculation results;
according to the modified calculation sequence and the consumption of a plurality of calculation results of the first attribute data according to a preset data buffer queue, converting the first attribute data into second attribute data in a preset format, extracting time sequence data in the second attribute data and sequencing;
performing feature extraction on the sequenced time sequence data to acquire dimension data of the time sequence data;
establishing a corresponding dimension coordinate system according to the dimension data;
acquiring a display instruction of a user;
and displaying a plurality of calculation results in a dimensional coordinate system according to the display instruction.
10. The comprehensive evaluation method based on the editable mesh index system according to claim 1, wherein after the incidence relation between the indexes to be evaluated is determined, the reliability of the incidence relation is calculated, and the incidence relation with the reliability lower than the preset reliability is marked;
the calculating the credibility of the association relationship comprises the following steps:
selecting an index to be evaluated as a confidence index, and acquiring an associated index having an associated relation with the confidence index according to the associated relation of the confidence index;
calculating the credibility K of the confidence index in the attribute set A1：
Wherein, baIs a confidence index; f1Is a membership function of the confidence index on the attribute set A; u is the discourse domain where the confidence index and the correlation index are located; n is the number of all indexes on the attribute set A; bxIs the x index on the attribute set A; t (b)a，bx) Similarity between the confidence index and the x index on the attribute set A is obtained;
calculating the credibility K of the correlation index in the relative attribute set (R-A)2：
Wherein, bcIs a correlation index; f2Is A membership function of the correlation index on A relative attribute set (R-A); m is the number of all indexes on the relative attribute set (R-A); byIs the y index on the relative attribute set (R-A); t (b)c，by) Similarity of the associated index and the y index on the relative attribute set (R-A) is taken as A similarity; r is the total attribute set;
credibility K in attribute set A according to confidence index1And offCredibility K of joint index in relative attribute set (R-A)2Calculating the reliability K of the association relation3：
And when the credibility of the association relation is less than the preset credibility, marking the association relation.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113590724A (en) * | 2021-08-03 | 2021-11-02 | 厦门至恒融兴信息技术股份有限公司 | Data index comprehensive management and visual evaluation method and system |
| CN114706743A (en) * | 2022-04-27 | 2022-07-05 | 中电普信(北京)科技发展有限公司 | Comprehensive evaluation method supporting real-time evaluation |
| CN117332923A (en) * | 2023-10-09 | 2024-01-02 | 北京京航计算通讯研究所 | Weighting method and system for netlike index system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113590724A (en) * | 2021-08-03 | 2021-11-02 | 厦门至恒融兴信息技术股份有限公司 | Data index comprehensive management and visual evaluation method and system |
| CN114706743A (en) * | 2022-04-27 | 2022-07-05 | 中电普信(北京)科技发展有限公司 | Comprehensive evaluation method supporting real-time evaluation |
| CN114706743B (en) * | 2022-04-27 | 2023-01-06 | 中电普信(北京)科技发展有限公司 | Comprehensive evaluation method supporting real-time evaluation |
| CN117332923A (en) * | 2023-10-09 | 2024-01-02 | 北京京航计算通讯研究所 | Weighting method and system for netlike index system |
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