CN111953543A - PCA-AHP-based quantum communication network reliability condition evaluation method - Google Patents
PCA-AHP-based quantum communication network reliability condition evaluation method Download PDFInfo
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Abstract
The invention relates to an evaluation method of the reliability condition of a quantum communication network, which is based on an improved principal component-analytic hierarchy process and comprises the following steps in sequence: screening evaluation indexes by adopting an analytic hierarchy process; establishing a quantum communication network evaluation index system by adopting an improved principal component analysis method; carrying out consistency and dimensionless processing on indexes in the evaluation index system; calculating the weight of the evaluation index by utilizing a Delphi method to obtain an evaluation function of the reliability condition of the quantum communication network; and evaluating the reliability condition of the quantum communication network according to the evaluation function. The evaluation method of the invention adds an improved principal component analysis method on the basis of an analytic hierarchy process, solves the problem of serious index subjectivity caused by the traditional expert opinion method, and ensures reasonable and objective multi-level model building of each index of the quantum communication network.
Description
Technical Field
The invention relates to the technical field of quantum communication networks, in particular to a quantum communication network index reliability assessment method based on principal component analysis-hierarchical analysis (PCA-AHP).
Background
Principal Component Analysis (PCA) is a statistical method for reducing dimensions. A group of variables with possible correlation is converted into a group of linearly uncorrelated variables through orthogonal transformation, the converted group of variables are called principal components, and the size of information is usually measured by a dispersion square sum or a variance. Principal component analysis is represented algebraically as transforming the covariance matrix of the original random vector into a diagonal matrix, geometrically as transforming the original coordinate system into a new orthogonal coordinate system, pointing to the p orthogonal directions where the sample points are most spread, then performing dimensionality reduction on the multidimensional variable system to convert the multidimensional variable system into a low-dimensional variable system with a higher precision, and further converting the low-dimensional system into a one-dimensional system by constructing a proper cost function.
An Analytic Hierarchy Process (AHP) is a hierarchical and structured decision method for analyzing a scheme multi-index system, and models and quantifies a decision thinking Process of a decision maker to a complex system. Generally, the analytic hierarchy process can be performed in the following four steps. Firstly, analyzing the relationship among all factors in the system and establishing a hierarchical structure of the system; secondly, comparing every two of the importance of each element of the same level about a certain criterion in the previous level, and constructing a judgment matrix for comparing every two of the elements; thirdly, calculating the relative weight of the compared elements to the criterion by the judgment matrix, and carrying out consistency check on the judgment matrix; and fourthly, calculating the total sorting weight of each hierarchy to the system and sorting. And finally, obtaining the total ordering of each scheme on the total target.
The core of the quantum communication network is a quantum key distribution technology, and in order to enable the quantum secure communication to be rapid, practical and industrialized, the normal distribution of the quantum key needs to be ensured, the service coverage and the system capacity required by wide application are provided, and higher requirements are provided for the reliability of the quantum communication network.
Disclosure of Invention
Generally, the reliability of a system is measured by the capability of the system to complete a specified function, and how to ensure the reliability of the quantum communication network in a specified time under specified conditions makes the reliability evaluation problem of the quantum communication network become the first solution problem when the whole network maintains the capability of quantum key distribution. Therefore, the invention provides a quantum communication network index reliability assessment method based on principal component analysis and hierarchical analysis.
In order to solve the technical problem of the reliability evaluation of the quantum communication network, the invention provides a quantum communication network index reliability evaluation method based on a principal component analysis method and an analytic hierarchy process. Therefore, the invention provides an evaluation method of the reliability condition of a quantum communication network, which is characterized in that the evaluation method is based on an improved principal component-analytic hierarchy process and comprises the following sequential steps:
-screening evaluation indicators using an analytic hierarchy process;
-establishing a quantum communication network evaluation index system using a modified principal component analysis method;
-the indices in the evaluation index system are subjected to a consensus and dimensionless processing;
-calculating a weight of the evaluation index using the delphi method to obtain an evaluation function of the reliability status of the quantum communication network;
-making an evaluation of the reliability status of the quantum communication network according to an evaluation function.
According to a preferred embodiment of the present invention, the analytic hierarchy process comprises the steps of:
analyzing the problem, extracting the factors related to the problem by principal component analysis, and analyzing the factors
Factor layering forms a hierarchy analysis chart;
-analyzing the relation between the indexes of the quantum communication network, and regarding the correlation between the indexes in a hierarchical structure
Making judgment on the degree to construct a judgment matrix;
and carrying out consistency check on the judgment matrix, reconstructing the judgment matrix when the consistency condition is not met, and calculating the weight when the consistency condition is met, thereby finally selecting the index which can be used for evaluating the reliability condition of the quantum communication network.
The core of the analytic hierarchy process for solving the problems is to simplify the complex problems by establishing a hierarchical structure and analyzing the relationship among the hierarchies. The hierarchical analysis graph structure comprises a target layer, a middle layer and an index layer, wherein for two adjacent layers, the high layer is called the target layer, and the low layer is called the index layer.
The analytic hierarchy process analyzes the relation among each index of the quantum communication network by constructing a judgment matrix, judges the relevant importance degree of the index according to the hierarchical structure, and selects the index which can be used for evaluating the reliability of the quantum communication network. That is, n subordinate indexes on the same layer are compared pairwise, and importance degree judgment is performed to form a matrix A, so that a judgment matrix A can be obtained as follows:
in the formula aijThe importance degree of the ith index to the jth index is shown.
And then, consistency check is carried out on the judgment matrix A, the consistency condition is met when the detection principle is that CR is less than 0.1, otherwise, the judgment matrix is reconstructed when the consistency condition is not met, wherein CR is CI/RCI, CI is (lambda max-n)/(n-1), lambda max is the maximum characteristic root of the matrix A, and RCI can be searched from a standard table.
Preferably, the hierarchical analysis map sequentially comprises a target layer, a middle layer and an index layer; after the judgment matrix is constructed, the subordinate indexes of the same layer are compared pairwise according to the hierarchical structure, so that the relative importance degree between the indexes is judged.
According to another preferred embodiment of the present invention, the improved principal component analysis method comprises the steps of:
-standardizing the matrix according to a network state evaluation index criterion matrix;
-computing feature roots and unit feature vectors, and computing principal component variance contribution rates and factor load quantities;
-selecting and analyzing the principal components;
screening out indexes for establishing a quantum communication network evaluation index system.
Preferably, the network state evaluation index criterion matrix is a quantum communication network reliability evaluation index selected according to the judgment matrix obtained in the analytic hierarchy process, and index parameters are respectively selected from the quantum communication network reliability evaluation index, each index parameter is quantized, and an index parameter quantization matrix is constructed, that is, X ═ X1, X2, X3], where:
x1: representing the percentage of the corresponding index parameter in the statistics of the first-class events (serious problems) of the past year;
x2: representing the percentage of the corresponding index parameter in the statistics of the secondary events (important problems) of the past year;
x3: representing the percentage of the corresponding index parameter in the statistics of the three-level events (general problems) of the calendar year.
The index parameters are projected into a coordinate system taking comprehensive evaluation as an axis, are sequentially arranged according to the weight of each index parameter, and the weight is used as a key parameter selection basis, so that the influence of monitoring data on results is avoided. Since the variable dimensions of the matrix are often different, the most common method is to normalize the raw data to eliminate the dimensional effect. I.e. the data is transformed as follows:
wherein:
And solving the correlation coefficient matrix, | lambda I-R | ═ 0, solving the eigenvalue of the matrix and the corresponding eigenvector, and sequencing the eigenvalue and the corresponding eigenvector according to the magnitude. The criteria for selecting the number of principal components is in accordance with the eigenvalues of the principal component vectors. If the eigenvalue of the principal component vector is less than a certain value, it means that it cannot interpret any index, so when selecting the eigenvalue, a factor with a large eigenvalue should be selected as the principal component.
Calculating the accumulated variance contribution rate and determining the number of the principal components, wherein the variance contribution rate reflects the data information content contained in each principal component after variable correlation transformation, and when the principal component contribution rate is larger, the data information content contained in the common factor is larger, and the factor is more important.
Variance contribution ratio:
cumulative variance contribution rate:
the cumulative variance contribution rate represents the amount of the original data information, generally, the number of the selected principal components needs to be selected to ensure that the cumulative contribution rate of the selected principal components should reach more than 85%, and it can be considered that the problem can be solved by analyzing the principal components while the original data information is retained.
Obtaining the main component load:
wherein: α 1, α 2, … α m are eigenvalues, λ 1, λ 2, … λ m are eigenvectors.
Calculating the index variable weight of each index, analyzing the selected m main components, calculating the weight H of each state index parameter in the main components, obtaining the weight of each state index parameter through calculation, and then sorting according to the size of each state index parameter, wherein the formula of the weight is as follows:
then, the weights of the obtained index parameters are normalized to [0,1], and the stronger the weight, the stronger the correlation of the state index parameters, indicating that the representativeness of the state index parameters is stronger.
According to still another preferred embodiment of the present invention, the calculating the weight of the evaluation index using the delphi method includes the steps of:
-collecting and scoring expert opinions in an anonymous manner a plurality of times;
-calculating the concentration of opinions E, as the average score value of the expert, by the formula:
-calculating the opinion dispersion by the formula:
in the formula: e is the concentration of opinions and the divergence degree of opinions;
-judging whether the inquiry is finished, setting the lower limit values E0 and 0 of concentration and opinion divergence according to the question, and stopping the inquiry when the following conditions are met: ei > E0, i > 0.
And finally, evaluating the health condition of the quantum communication network according to the evaluation function value.
According to a preferred embodiment of the present invention, the evaluation of the reliability condition of the quantum communication network according to the evaluation function is to select a corresponding evaluation method and evaluation model, and analyze the evaluation results of each index of the quantum communication network according to the selected evaluation method and evaluation model. After indexes of each layer are obtained by an improved principal component analysis method and an improved analytic hierarchy method, and the index weight of a Delphi method is calculated, the reliability condition of the quantum communication network is evaluated according to an evaluation function value:
-collecting quantum communication network data: including operating parameters and equipment data, etc.;
-statistical analysis of data: carrying out statistical analysis on the quantum communication network data to obtain the value of a single index;
-calculating a single indicator score: substituting the single index value into a single index scoring formula to obtain a single index score;
-calculating a criterion layer indicator score and a target layer indicator score: if an analytic hierarchy process is selected, then the method is based on
The score and the weight factor of the item index are calculated layer by layer, and the formula is as follows:
in the formula: s(K+1)Representing a certain index A of 1 layer k in the hierarchy(K+1)Scoring of (4); n represents an index A(K+1)The number of k layers of sub-indices;
is represented by A(K+1)The score of k-layer sub-index j;
is represented by A(K+1)The weight of k layers of sub-indices j;
-quantum communication network reliability assessment result: a percentile system is generally used, where the evaluation score is divided into four levels, respectively "good", "medium" and "poor", where a score of >90 is "good", a 90> score of >70 is "good", a 70> score of >60 is "medium", and a score of <60 is "poor". Analyzing weak links of the quantum communication network: firstly, analyzing a macro index (target layer), if the index score is 'middle' or 'poor', finding out a weak link of the operation of the macro index according to the score of a single index, and finally, providing corresponding improvement measures.
Preferably, the evaluation method further comprises a statistical step before implementing each step, wherein the statistical step is to analyze the quantum communication network index data of the past year, analyze and preliminarily evaluate the quantum communication network index data of the past year, and then establish a corresponding evaluation model of the quantum communication network through the historical data.
According to the quantum communication network index reliability assessment method based on principal component analysis and hierarchical analysis, an improved principal component analysis method is added on the basis of the hierarchical analysis method, the problem that index subjectivity is serious due to the fact that an expert opinion method is used in the traditional method is solved, reasonable and objective multilayer model building of each index of a quantum communication network is guaranteed, correlation of each index of the quantum communication network can be analyzed, index redundancy is reduced, and efficiency and analysis accuracy in quantum communication network index reliability assessment are greatly improved.
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The invention will be better understood from reading the following examples, given by way of example only (without any limitative nature) and with reference to the accompanying drawings, in which:
fig. 1 is a flow chart of quantum communication network evaluation based on improved principal component-hierarchy analysis according to an embodiment of the present invention.
FIG. 2 is a flow diagram of an improved principal component analysis method according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to specific embodiments and the accompanying drawings. Those skilled in the art will appreciate that the present invention is not limited to the drawings and the following examples.
The embodiment of the invention provides a quantum communication network evaluation method based on improved principal component-level analysis. The stable operation of the quantum communication network is the most basic requirement, the service interruption fault of the quantum communication network can influence the key distribution, so that a large amount of business and economic losses are caused, and even the safety of countries and enterprises is influenced in severe cases, so that the process control indexes of the quantum communication network need to be decomposed and controlled, and the process control index parameters which obviously influence the quantum communication network are obtained, so that the quantum communication network can be managed in a targeted manner, and the reliability and the stability of the quantum communication network can be effectively improved.
In the present embodiment (see fig. 1 and fig. 2), in order to accurately evaluate the comprehensive state of the quantum communication network, an analytic hierarchy process is adopted to screen indexes, and a principal component analysis process is adopted to establish an evaluation index system of the quantum communication network; secondly, carrying out consistency and dimensionless processing on the indexes; and then, calculating the weight by utilizing a Delphi method to obtain a reliability condition evaluation function of the quantum communication network, and finally evaluating the reliability condition of the quantum communication network according to the evaluation function value.
The implementation mode is based on quantum communication network evaluation of improved principal component-level analysis, so that index selection under different networks and different requirements can be fully considered in the process of selecting evaluation indexes, meanwhile, the selected indexes can be verified and screened, indexes with repeated expression information are removed on the premise of not losing a large amount of monitoring data, and the indexes capable of most expressing network states are extracted.
1. And constructing an evaluation index system by a principal component analysis method and an analytic hierarchy process, and selecting the most key indexes in the operation of the quantum communication network.
The core of the analytic hierarchy process for solving the problems is to simplify the complex problems by establishing a hierarchical structure and analyzing the relationship among the hierarchies. The hierarchical analysis graph structure comprises a target layer, a middle layer and an index layer, wherein for two adjacent layers, the upper layer is called the target layer, and the lower layer is called the index layer (see the following table).
The analytic hierarchy process analyzes the relation among each index of the quantum communication network by constructing a judgment matrix, judges the relevant importance degree of the index according to the hierarchical structure, and selects the index which can be used for evaluating the reliability of the quantum communication network. That is, n subordinate indexes on the same layer are compared pairwise, and importance degree judgment is performed to form a matrix A, so that a judgment matrix A can be obtained as follows:
in the formula aijThe importance degree of the ith index to the jth index is shown.
And then, consistency check is carried out on the judgment matrix A, the consistency condition is met when the detection principle is that CR is less than 0.1, otherwise, the judgment matrix is reconstructed when the consistency condition is not met, wherein CR is CI/RCI, CI is (lambda max-n)/(n-1), lambda max is the maximum characteristic root of the matrix A, and RCI can be searched from a standard table.
The improved principal component analysis method comprises (in conjunction with the flow chart shown in fig. 2): according to the network state evaluation index criterion matrix, carrying out standardization processing on the matrix; calculating characteristic roots and unit characteristic vectors, calculating the variance contribution rate and the factor load capacity of the principal components, selecting the principal components, analyzing the principal components, and screening out index parameters. The network state evaluation index criterion matrix is that index parameters are respectively selected from the reliability evaluation indexes of the quantum communication network selected according to the judgment matrix a, each index parameter is quantized, and an index parameter quantization matrix is constructed, namely X ═ X1, X2, and X3.
The index parameters are projected into a coordinate system taking comprehensive evaluation as an axis, are sequentially arranged according to the weight of each index parameter, and the weight is used as a key parameter selection basis, so that the influence of monitoring data on results is avoided. Since the variable dimensions of the matrix are often different, the most common method is to normalize the raw data to eliminate the dimensional effect. I.e. the data is transformed as follows:
wherein:
according to the principle of covariance, after any variable is subjected to standardization transformation, a variable covariance matrix obtained by standardizing a data matrix is a correlation coefficient matrix of the variable covariance matrix, and the standardized covariance correlation coefficient is equivalent.
And solving the correlation coefficient matrix, | lambda I-R | ═ 0, solving the eigenvalue of the matrix and the corresponding eigenvector, and sequencing the eigenvalue and the corresponding eigenvector according to the magnitude. The criteria for selecting the number of principal components is in accordance with the eigenvalues of the principal component vectors. If the eigenvalue of the principal component vector is less than a certain value, it means that it cannot interpret any index, so when selecting the eigenvalue, a factor with a large eigenvalue should be selected as the principal component.
Calculating the accumulated variance contribution rate and determining the number of the principal components, wherein the variance contribution rate reflects the data information content contained in each principal component after variable correlation transformation, and when the principal component contribution rate is larger, the data information content contained in the common factor is larger, and the factor is more important.
Variance contribution ratio:
cumulative variance contribution rate:
the cumulative variance contribution rate represents the amount of the original data information, generally, the number of the selected principal components needs to be selected to ensure that the cumulative contribution rate of the selected principal components should reach more than 85%, and it can be considered that the problem can be solved by analyzing the principal components while the original data information is retained.
Obtaining the main component load:
wherein: α 1, α 2, … α m are eigenvalues, λ 1, λ 2, … λ m are eigenvectors.
Calculating the index variable weight of each index, analyzing the selected m main components, calculating the weight H of each state index parameter in the main components, obtaining the weight of each state index parameter through calculation, and then sorting according to the size of each state index parameter, wherein the formula of the weight is as follows:
then, the weights of the obtained index parameters are normalized to [0,1], and the stronger the weight, the stronger the correlation of the state index parameters, indicating that the representativeness of the state index parameters is stronger.
2. Determining the weight of the evaluation index by a Delphi method, determining a reliability evaluation function of the quantum communication network, calculating the weight by the Delphi method, and obtaining a health condition evaluation function of the quantum communication network, wherein the health condition evaluation function is as follows: the expert scoring method is also called the delphi method, and is a method for comprehensively and comprehensively evaluating a certain event by integrating the experience, knowledge and opinion of experts in the same field. The method is carried out in an anonymous mode when the experience, knowledge and opinion of the experts are collected, so that the experts are ensured not to interfere with each other when making decisions, blind follow and accompanying phenomena are avoided, and the expert opinions need to be consulted for many times.
The specific implementation mode is as follows: calculating the opinion concentration E according to the following formula as the average score value of the expert:
and then calculating the opinion dispersion, namely, a standard calculation formula is shown as the following formula:
in the formula: e is the concentration of opinions and the degree of divergence of opinions.
Then judging whether the inquiry is finished or not, setting lower limit values E0 and 0 of concentration and opinion divergence according to the problems, and stopping the inquiry when the following conditions are met: ei > E0, i > 0.
And finally, evaluating the health condition of the quantum communication network according to the evaluation function value.
3. And selecting an evaluation method and an evaluation model to evaluate the reliability of the quantum communication network.
After the indexes of each layer are obtained according to the improved principal component analysis method and the improved analytic hierarchy method and the index weight of the Delphi method is calculated, the reliability condition of the quantum communication network is evaluated according to the evaluation function value:
collecting index data: the method comprises the steps of quantum communication network operation parameters, network data and the like;
data statistical analysis: carrying out statistical analysis on the operation parameters of the quantum communication network and the network data to obtain the value of a single index;
calculating the score of the single index: substituting the single index value into a single index scoring formula to obtain a single index score;
calculating an intermediate layer index score and a target layer index score: if the selected analytic hierarchy process is adopted, the calculation is carried out layer by layer according to the score and the weight factor of the single index, and the formula is as follows:
in the formula: s(K+1)Representing a certain index A of 1 layer k in the hierarchy(K+1)Scoring of (4); n represents an index A(K+1)The number of k layers of sub-indices;
is represented by A(K+1)The score of k-layer sub-index j;
is represented by A(K+1)K layers of sub-indices j.
The reliability evaluation result of the quantum communication network is as follows: a percentile system is generally used, where the evaluation score is divided into four levels, respectively "good", "medium" and "poor", where a score of >90 is "good", a 90> score of >70 is "good", a 70> score of >60 is "medium", and a score of <60 is "poor".
Analyzing weak links of the quantum communication network: firstly, analyzing a macro index (target layer), if the index score is 'middle' or 'poor', finding out a weak link of the operation of the macro index according to the score of a single index, and finally, providing corresponding improvement measures.
The quantum communication network evaluation method based on the improved principal component analysis and the hierarchical analysis provided by the embodiment adds the improved principal component analysis method on the basis of the traditional hierarchical analysis method, then performs index weight calculation of each level according to the delphif method to obtain a health condition evaluation function of the quantum communication network, and finally evaluates the health condition of the quantum communication network according to the evaluation function value. The problem of serious index subjectivity caused by the traditional expert opinion method is solved, reasonable and objective multi-level model building of each index of the quantum communication network is guaranteed, the correlation of each index of the quantum communication network can be analyzed, index redundancy is reduced, and efficiency and precision of quantum communication network evaluation are greatly improved.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Term list
Principal Component Analysis (PCA)
AHP: and (5) performing hierarchical analysis.
Claims (8)
1. An evaluation method of the reliability condition of a quantum communication network, characterized in that the evaluation method is based on an improved principal component-analytic hierarchy process and comprises the following sequential steps:
-screening evaluation indicators using an analytic hierarchy process;
-establishing a quantum communication network evaluation index system using a modified principal component analysis method;
-the indices in the evaluation index system are subjected to a consensus and dimensionless processing;
-calculating a weight of the evaluation index using the delphi method to obtain an evaluation function of the reliability status of the quantum communication network;
-making an evaluation of the reliability status of the quantum communication network according to an evaluation function.
2. The evaluation method of claim 1, wherein the analytic hierarchy process comprises the steps of:
-analyzing the problem, extracting factors related to the problem by principal component analysis, and layering the factors to form a layer analysis graph;
analyzing the relation among various indexes of the quantum communication network, and judging the relevant importance degree among the indexes according to a hierarchical structure so as to construct a judgment matrix;
and carrying out consistency check on the judgment matrix, reconstructing the judgment matrix when the consistency condition is not met, and calculating the weight when the consistency condition is met, thereby finally selecting the index which can be used for evaluating the reliability condition of the quantum communication network.
3. The evaluation method according to claim 2, wherein the hierarchical analysis graph includes a target layer, an intermediate layer, and an index layer in this order; after the judgment matrix is constructed, the subordinate indexes of the same layer are compared pairwise according to the hierarchical structure, so that the relative importance degree between the indexes is judged.
4. The evaluation method according to claim 1, wherein the improved principal component analysis method comprises the steps of:
-standardizing the matrix according to a network state evaluation index criterion matrix;
-computing feature roots and unit feature vectors, and computing principal component variance contribution rates and factor load quantities;
-selecting and analyzing the principal components;
screening out indexes for establishing a quantum communication network evaluation index system.
5. The evaluation method of claim 4, wherein the network state evaluation index criterion matrix is a quantum communication network reliability evaluation index selected according to the judgment matrix obtained in the analytic hierarchy process, and index parameters are respectively selected from the matrix, and each index parameter is quantized to construct an index parameter quantization matrix, i.e. X ═ X1, X2, X3], where:
x1: representing the percentage of the corresponding index parameter in the serious problem statistics of the first-level events in the past year;
x2: representing the percentage of the corresponding index parameters in the statistics of the important problems of the secondary events in the past year;
x3: and the percentage of the corresponding index parameter in the general problem statistics of the three-level events of the past year is represented.
6. The evaluation method according to claim 1, wherein the calculating of the weight of the evaluation index using the delphi method includes the steps of:
-collecting and scoring expert opinions in an anonymous manner a plurality of times;
-calculating the concentration of opinions E, as the average score value of the expert, by the formula:
-calculating the opinion dispersion by the formula:
in the formula: e is the concentration of opinions and the divergence degree of opinions;
-judging whether the inquiry is finished, setting the lower limit values E0 and 0 of concentration and opinion divergence according to the question, and stopping the inquiry when the following conditions are met: ei > E0, i > 0.
7. The evaluation method according to claim 1, wherein the evaluation of the reliability condition of the quantum communication network according to the evaluation function comprises the steps of selecting a corresponding evaluation method and evaluation model, and analyzing evaluation results of various indexes of the quantum communication network according to the selected evaluation method and evaluation model:
-collecting quantum communication network data: including operating parameters and equipment data, etc.;
-statistical analysis of data: carrying out statistical analysis on the quantum communication network data to obtain the value of a single index;
-calculating a single indicator score: substituting the single index value into a single index scoring formula to obtain a single index score;
-calculating a criterion layer indicator score and a target layer indicator score: if the selected analytic hierarchy process is adopted, the calculation is carried out layer by layer according to the score and the weight factor of the single index, and the formula is as follows:
in the formula: s(K+1)Representing a certain index A of 1 layer k in the hierarchy(K+1)Scoring of (4); n representsIndex A(K+1)The number of k layers of sub-indices;
is represented by A(K+1)The score of k-layer sub-index j;
is represented by A(K+1)The weight of k layers of sub-indices j;
analyzing the weak link of the quantum communication network operation, and finally providing corresponding improvement measures.
8. The evaluation method according to claim 1, wherein the evaluation method further comprises a statistical step before implementing the steps, wherein the statistical step is to analyze the historical quantum communication network index data, perform analysis and preliminary evaluation on the historical quantum communication network index data, and then establish an evaluation model of the corresponding quantum communication network through historical data.
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