CN113657736B

CN113657736B - Dynamic weapon equipment system efficiency evaluation method based on structural equation model

Info

Publication number: CN113657736B
Application number: CN202110891190.0A
Authority: CN
Inventors: 熊伟; 韩驰; 简平; 刘德生; 熊明晖; 刘正; 刘文文; 于小岚
Original assignee: Peoples Liberation Army Strategic Support Force Aerospace Engineering University
Current assignee: Peoples Liberation Army Strategic Support Force Aerospace Engineering University
Priority date: 2021-08-04
Filing date: 2021-08-04
Publication date: 2022-10-14
Anticipated expiration: 2041-08-04
Also published as: CN113657736A

Abstract

The invention provides a dynamic evaluation method, a system, a device and electronic equipment for the efficiency of a weapon equipment system based on a structural equation model, which comprises the following steps: s101, analyzing the characteristics of an evaluation object and evaluation requirements to generate a planned space of an equipment fighting scheme, S102, analyzing efficiency indexes corresponding to all subsystems of an equipment system in the equipment composition scheme, and constructing an equipment efficiency evaluation index system; s103, dividing the indexes into an exogenous variable X and an endogenous variable Y; dividing the bottom layer index into an exogenous latent variable xi and dividing the secondary index into an endogenous latent variable eta according to whether the index data is directly acquired or not; s104, establishing a linear structure equation model and a nonlinear structure equation model for battle efficiency evaluation according to the mapping relation among the exogenous apparent variable X, the endogenous apparent variable Y, the exogenous latent variable xi and the endogenous latent variable eta; s105, the analytical model is used for solving the result of operational effectiveness; and S106, analyzing the result of the combat effectiveness and obtaining an evaluation conclusion. The problems of insufficient objectivity and poor evaluation accuracy and credibility in the prior art are solved.

Description

Dynamic weapon equipment system efficiency evaluation method based on structural equation model

Technical Field

The present disclosure relates to the field of effective evaluation technologies, and in particular, to a system, a method, a device, and an electronic device for dynamically evaluating the effectiveness of a weaponry system based on a structural equation model.

Background

The weapon equipment system is an open complex system, informatization and intellectualization are basic characteristics of a modern weapon equipment system, various interacting weapon equipment are combined into an organic whole to form a complex weapon equipment system, and the fighting efficiency of the equipment system presents complex nonlinear characteristics. Meanwhile, the fighting process has violent antagonism and dynamics, and how to effectively process the characteristics of nonlinearity, antagonism and dynamics of the fighting efficiency of a complex equipment system is one of the core problems of the efficiency evaluation of the equipment system.

At present, the traditional effectiveness evaluation methods such as a combat simulation method, an analytic method and an expert evaluation method evaluate the effectiveness of a complex equipment system from different angles, but the problems of poor reliability of an evaluation model, high difficulty in extracting index data, excessive dependence on subjective experience and the like generally exist. Therefore, the conventional evaluation method is no longer suitable for performance evaluation of complex equipment system. Under the framework of a structural equation model method, the structural equation model is introduced into efficiency evaluation, and simulation data under the condition of dynamic confrontation of an evaluation object is obtained by combining a system dynamics simulation method, so that the defects of subjective experience dependence, antagonistic property and dynamic characterization deficiency of the traditional method are overcome.

For a traditional structural equation model method, the method is usually applied to the fields of psychology and sociology, a questionnaire survey mode is adopted to obtain data to solve a parametric equation, and the structural equation model is directly combined with equipment combat effectiveness less. In the invention, the explicit variable of the structural equation model corresponds to the bottom layer performance index of the equipment performance evaluation, and the latent variable corresponds to the performance index of the equipment performance evaluation, so that the one-to-one correspondence between the necessary structure of the structural equation model and the performance evaluation data is realized, and the performance evaluation can obtain a more accurate evaluation result by means of the advantage of the structural equation model reflecting the coupling interaction.

For the data acquisition method in the application step of the structural equation model, the traditional method mainly comprises questionnaire survey and the like, and is not suitable for the field of equipment efficiency evaluation. Aiming at the problems of high difficulty in acquiring evaluation data of equipment tests and the like, the invention adopts a system dynamics simulation method. However, in the traditional system dynamics model construction process, all relevant factors are directly added into the causal relationship loop and the stock flow chart. The inventory flow chart constructed in the mode has large scale and numerous factors, and influence relationships among the factors are complicated and complicated, so that the problems of complicated mathematical relationships among the influence factors, high tracing analysis difficulty and the like are caused.

After the structural equation model is applied to equipment efficiency evaluation, judgment of data of the linear structural equation model and the nonlinear structural equation model influences evaluation accuracy. In the traditional structural equation model, only a linear model is generally analyzed or a nonlinear model is singly used, so that the waste of evaluation data and the loss of evaluation elements are caused, and the evaluation result can hardly accurately reflect the objective actual characteristics of an evaluation object. For how to comprehensively use the analytical results of linear and nonlinear structural equation models, the related research results are still few at present.

Disclosure of Invention

The invention aims to provide a dynamic evaluation system, a method, equipment and electronic equipment for the efficiency of a weaponry system based on a structural equation model, and the dynamic evaluation system for the efficiency of the weaponry system based on the structural equation model can solve the problems of insufficient objectivity and poor evaluation accuracy and credibility in the prior art.

In order to achieve the above purpose, the invention provides the following technical scheme:

a dynamic evaluation method for the effectiveness of a weaponry system based on a structural equation model specifically comprises the following steps:

s101, analyzing the characteristics of an evaluation object and evaluation requirements to generate a planned space of an equipment fighting scheme, wherein the planned space comprises a scheme formed by a plurality of equipment;

s102, analyzing efficiency indexes corresponding to all the subsystems of the equipment system in the equipment composition scheme from a structural view by adopting a system analysis method under the background of integrated combined combat, screening according to an index system construction principle, and constructing an equipment efficiency evaluation index system by combining qualitative relationships among all the subsystems;

s103, dividing the index into an exogenous variable X and an endogenous variable Y according to the equipment efficiency evaluation index system and according to whether the index is determined by the factor of the index; dividing bottom layer indexes into exogenous latent variables xi and dividing secondary indexes into endogenous latent variables eta according to whether the index data are directly acquired or not;

s104, establishing a linear structure equation model and a nonlinear structure equation model for battle efficiency evaluation according to the mapping relation among the exogenous apparent variable X, the endogenous apparent variable Y, the exogenous latent variable xi and the endogenous latent variable eta;

s105, performing parameter estimation on the linear structure equation model and the nonlinear structure equation model respectively, judging whether the parameter estimation result evaluation index meets the judgment standard, if so, obtaining an analysis model of the efficiency index, wherein the analysis model is used for solving the combat efficiency result;

and S106, analyzing the result of the combat effectiveness and obtaining an evaluation conclusion.

On the basis of the technical scheme, the invention can be further improved as follows:

further, the S103 specifically includes:

s1031, designing mapping relations between bottom layer indexes in the equipment efficiency evaluation index system and corresponding latent variables and explicit variables of the structural equation model;

s1032, establishing a dynamic model of a basic flow rate tree entering system reflecting the complex equipment fighting process;

s1033, designing a mathematical model of each node;

s1034, operating the constructed dynamic model to obtain combat simulation data of different equipment composition schemes.

Further, the S104 specifically includes:

s1041, establishing a nonlinear structural equation model for fighting capacity evaluation according to the mapping relation between the bottom layer indexes and the latent variables and the obvious variables of the structural equation model;

s1042, converting the aggregation relation between the efficiency index and the capability index into an analytic model through parameter estimation of the model;

s1043, solving the fighting efficiency of different equipment composition schemes by using an analytic model;

and S1044, analyzing the result of the operational effectiveness, giving an evaluation conclusion and determining an equipment configuration scheme with the optimal operational effectiveness.

A dynamic evaluation system for effectiveness of a weaponry system based on a structural equation model, comprising:

the scheme generation module is used for analyzing the characteristics of the evaluation object and the evaluation requirement to generate a planned space of the equipment fighting scheme, and the planned space comprises a plurality of equipment composition schemes;

the equipment efficiency evaluation index system building module is connected with the scheme generating module and used for analyzing the efficiency indexes corresponding to all the subsystems of the equipment system in the equipment composition scheme from the structural view angle by adopting a system analysis method under the integrated combined combat background, screening according to an index system building principle and building an equipment efficiency evaluation index system by combining the qualitative relation among the subsystems;

the combat simulation data acquisition module is connected with the scheme generation module and the equipment efficiency evaluation index system and is used for dividing the indexes into an exogenous variable X and an endogenous variable Y according to the equipment efficiency evaluation index system and whether the factors of the equipment efficiency evaluation index system are determined; dividing bottom layer indexes into exogenous latent variables xi and dividing secondary indexes into endogenous latent variables eta according to whether the index data are directly acquired or not;

the operational efficiency evaluation module is connected with the operational simulation data acquisition module and is used for establishing a linear structure equation model and a nonlinear structure equation model for operational efficiency evaluation according to the mapping relation among the exogenous apparent variable X, the endogenous apparent variable Y, the exogenous latent variable xi and the endogenous latent variable eta;

the covariance structural model is connected with the operational effectiveness evaluation module, and is used for respectively carrying out parameter estimation on the linear structural equation model and the nonlinear structural equation model, judging whether the evaluation index of the parameter estimation result meets the judgment standard, if so, obtaining an analytic model of the effectiveness index, and the analytic model is used for solving the operational effectiveness result;

and the analysis module is connected with the covariance structure model and used for analyzing the combat effectiveness result and obtaining an evaluation conclusion.

Further, the combat simulation data acquisition module is further configured to:

designing a mapping relation between bottom layer indexes in an equipment efficiency evaluation index system and corresponding latent variables and explicit variables of a structural equation model;

establishing a dynamic model of a basic flow rate tree-entering system reflecting the complex equipment fighting flow;

designing a mathematical model of each node;

and operating the constructed dynamic model to obtain combat simulation data of different equipment composition schemes.

Further, the combat effectiveness evaluation module is further configured to:

establishing a nonlinear structural equation model for evaluating the operational capacity according to the mapping relation between the underlying indexes and the latent variables and the apparent variables of the structural equation model;

converting the aggregation relation between the efficiency index and the capability index into an analytic model through parameter estimation of the model;

solving the fighting efficiency of different equipment composition schemes by using an analytical model;

and analyzing the result of the operational effectiveness, giving an evaluation conclusion, and determining an equipment allocation scheme with the optimal operational effectiveness.

A dynamic evaluation device for the effectiveness of a weaponry system based on a structural equation model comprises: the system comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the computer program when executed by the processor implements the steps of the dynamic evaluation method for the effectiveness of the weaponry system based on a structural equation model.

An electronic device, wherein an information transfer implementation program is stored on the electronic device, and when the program is executed by a processor, the steps of the dynamic evaluation method for the effectiveness of the weaponry system based on a structural equation model are implemented.

The invention has the following advantages:

according to the dynamic evaluation method for the efficiency of the weapon equipment system based on the structural equation model, the structural equation model is used for evaluating the fighting efficiency of the equipment system, the characteristic of interactive coupling inside the equipment system is considered, a secondary term and an interactive term are proposed to be introduced, the efficiency of the complex equipment system is evaluated by the nonlinear structural equation model, and the accuracy and the credibility of evaluation are improved. In order to improve the quality of evaluation data, the mapping relation between each layer of index in a design index system and variable types such as a display variable, a latent variable and the like is provided, the reliability of a data source is improved by adopting a system dynamics model method to generate combat simulation data, and the dynamics and the antagonism of a combat process can be more accurately reflected. The problems of insufficient objectivity and poor evaluation accuracy and credibility in the prior art are solved.

Drawings

In order to more clearly illustrate one or more embodiments or prior art solutions of the present specification, the drawings that are needed in the description of the embodiments or prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and that other drawings can be obtained by those skilled in the art without inventive exercise.

FIG. 1 is a flow chart of a method for dynamically evaluating the effectiveness of a weaponry system based on a structural equation model according to an embodiment of the present invention;

fig. 2 is a detailed flowchart of S103;

fig. 3 is a detailed flowchart of S104;

FIG. 4 is a table diagram of structural equation model variable partitioning;

FIG. 5 is a table of linear SEM parameter estimates;

FIG. 6 is a tabular representation of linear SEM partial fit indices;

FIG. 7 is a tabular representation of non-linear SEM partial fit indices;

FIG. 8 is a schematic diagram of the fit metric evaluation criteria;

FIG. 9 is a flow chart of the fighting performance evaluation of the equipment system based on the nonlinear structural equation model;

FIG. 10 is a flow chart of the performance evaluation index system construction;

FIG. 11 is a schematic diagram of the constructed equipment system combat effectiveness evaluation index system;

FIG. 12 is a schematic diagram of a combat effectiveness linear metric structural equation model;

FIG. 13 is a schematic diagram of a combat effectiveness nonlinear metrology structural equation model;

FIG. 14 is a schematic diagram of a linear measure of operational effectiveness structural equation base model after parameter estimation;

FIG. 15 is a schematic diagram of a tactical performance nonlinear metric structural equation base model after parameter estimation;

fig. 16 is a schematic diagram of an apparatus for dynamically evaluating the effectiveness of a weaponry system based on structural equation models in an embodiment of the present invention.

Memory 10, processor 20.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in one or more embodiments of the present disclosure, the technical solutions in one or more embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in one or more embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all embodiments. All other embodiments that can be derived by a person skilled in the art from one or more of the embodiments described herein without making any inventive step shall fall within the scope of protection of this document.

As shown in fig. 1, a method for dynamically evaluating the effectiveness of a weaponry system based on a structural equation model specifically includes:

s101, generating a planned space of an equipment combat scheme;

analyzing the characteristics of an evaluation object and evaluation requirements to generate a planned space of an equipment fighting scheme, wherein the planned space comprises a plurality of equipment composition schemes;

each equipment composition scheme includes the type and number of elements, and the like. The performance evaluation of the equipment is an evaluation of the capabilities of these solutions.

As shown in fig. 10, S102, an equipment performance evaluation index system is constructed;

in the step, the system analysis method is adopted to analyze the efficiency indexes corresponding to all the subsystems of the equipment system in the equipment composition scheme from the structural view angle under the background of integrated combined combat, screening is carried out according to the index system construction principle, and an equipment efficiency evaluation index system is constructed by combining the qualitative relationship among all the subsystems;

firstly, analyzing an evaluation object from the composition structure and the essential elements of the evaluation object, and determining an evaluation index set; secondly, analyzing and evaluating the purpose to determine the structural relationship of the indexes;

determining an initial index system according to the relation between the index set and the index structure, screening indexes according to an index system construction principle, and performing rationality evaluation on the screened index system; and if the index system is reasonable, completing the construction of the efficiency evaluation index system. Taking the space-based information system as an example, the constructed index system is shown in fig. 11.

S103, dividing indexes;

in the step, according to an equipment efficiency evaluation index system, dividing indexes into an exogenous variable X and an endogenous variable Y according to whether the indexes are determined by self elements or not; dividing the bottom layer index into an exogenous latent variable xi and dividing the secondary index into an endogenous latent variable eta according to whether the index data is directly acquired or not;

and constructing a combat effectiveness evaluation model based on a structural equation model. First, the explicit and latent variables are determined. According to the performance measurement index of the constructed equipment system, the performance of the whole system is influenced by the performance of several sub-system indexes. To measure the effectiveness of a combat, the combat capability index is set as a latent variable. The command control capability, the survival guarantee capability and the information acquisition capability are determined by the elements of the system and are not influenced by other factors, so that the command control capability, the survival guarantee capability and the information acquisition capability are set as exogenous variables. The performance of the fire striking ability is affected by three exogenous variables, and thus, it is determined as an endogenous variable.

On the basis of selecting SEM latent variables (combat capability indexes), taking performance indexes corresponding to various combat capabilities as the display variables of the SEM. The division of the latent variable from the explicit variable is accomplished as shown in FIG. 4.

S104, establishing a linear structure equation model and a nonlinear structure equation model;

in the step, a linear structure equation model and a nonlinear structure equation model for operational effectiveness evaluation are established according to the mapping relation among an exogenous apparent variable X, an endogenous apparent variable Y, an exogenous latent variable xi and an endogenous latent variable eta;

and establishing an SEM measurement model. Analysis of internal latent variable eta and external latent variable xi ₁ 、ξ ₂ 、ξ ₃ The association relationship of (2). Because the latent variables may have linear and nonlinear correlation at the same time, the linear and nonlinear combat effectiveness measurement structural equation models are respectively established.

In a linear structure equation model, an endogenous latent variable eta and an exogenous latent variable xi ₁ 、ξ ₂ 、ξ ₃ The relationship of (c) is a linear relationship. A combat performance linear SEM was established on this basis, as shown in fig. 12. Wherein,

are respectively xi ₁ And x ₁ 、x ₂ 、x ₃ The coefficient of the path between the two paths,

is xi ₂ And x ₄ 、x ₅ The coefficient of the path between the two antennas,

is xi ₃ And x ₆ 、x ₇ The coefficient of the path between the two paths,

are η and y respectively ₁ 、y ₂ 、y ₃ Coefficient of inter-path, gamma ₁ 、γ ₂ 、γ ₃ Is xi ₁ 、ξ ₂ 、ξ ₃ Path coefficient between eta and eta, phi ₁₂ 、φ ₂₃ Are respectively xi ₁ 、ξ ₂ And xi ₂ 、ξ ₃ Coefficient of correlation between, delta ₁ ～δ ₇ Is x ₁ ～x ₇ Of the error parameter epsilon ₁ ～ε ₃ Is y ₁ ～y ₃ ζ is an error parameter of η.

In a nonlinear structural equation model, the invention contemplates an installationCoupling interaction existing between the backup systems and correlation interaction existing between the indexes are adopted, and xi in SEM is linearly measured ₁ 、ξ ₂ 、ξ ₃ And eta are difficult to describe the complementary and cooperative relationship among the system capabilities. In order to more accurately depict the mutual influence among all elements in the system, the internal latent variable eta and the external latent variable xi in the linear SEM ₁ 、ξ ₂ 、ξ ₃ On the basis of linear correlation, the addition of xi is considered ₁ 、ξ ₂ 、ξ ₃ And (3) an inter-nonlinear term. On the basis of balancing the cost and the accuracy of the experiment, the invention uses the secondary term and the product term to depict the coupling interaction in the system and establishes a nonlinear measurement SEM of the combat effectiveness, as shown in figure 13.

S105, analyzing the model to solve the result of the operational effectiveness;

in the step, parameter estimation is respectively carried out on the linear structure equation model and the nonlinear structure equation model, whether the evaluation index of the parameter estimation result meets the judgment standard or not is judged, if yes, an analytical model of the effectiveness index is obtained, and the analytical model is used for solving the result of the combat effectiveness;

and judging the identifiability of the model. In SEM, when the numbers of the internal and external occurrence variables Y and X are p and q, respectively, the covariance and the variance can be generated in total

Namely contain

A system of equations. To ensure the identifiability of the model, the total number t of the path coefficients and the error terms to be estimated needs not to be more than the number of equations, namely:

the decision model may be identified when this condition is satisfied.

For a linear SEM, the number of endogenous significance variables p =3, the number of exogenous significance variables q =7, and the number of parameters to be estimated t =26.

Satisfies the identifiability judgment condition

The decision model may be identified.

For the nonlinear SEM, due to the introduction of the influence of the internal interaction effect and the secondary effect of the exogenous latent variable, the number of the parameters to be estimated is t =88, the number of the endogenous dominant variables is still p =3, and the number of the exogenous dominant variables is q =30. Satisfies the identifiability judgment condition

The model may be identified.

S106, analyzing the result of the combat effectiveness and obtaining an evaluation conclusion;

in this step, the result of the operational effectiveness is analyzed and an evaluation conclusion is obtained.

And (5) constructing a parameter equation.

The measurement equation of the combat effectiveness linear measurement structural equation model is as follows:

the model structural equation is:

η＝γ ₁ ξ ₁ +γ ₂ ξ ₂ +γ ₃ ξ ₃ +ζ

the measurement equation of the combat effectiveness nonlinear measurement structure equation model is as follows:

the corresponding model structural equation is:

and (5) constructing a system dynamics model. A system dynamics method is adopted to simulate the battle process of a complex equipment system, and simulation data and a system dynamics model under the dynamic confrontation condition are provided. And taking entities in the equipment system as model nodes, and constructing an internode mathematical model by using the relation between the entities. Taking the evaluation background of the invention as an example, according to the definition of the inventory flow in the system dynamics, the inventory is the accumulation of time and is directly determined by the flow, so the mathematical equation of the number of the blue-square surface ships and the loss rate is obtained as follows:

wherein, N _b (t) the number of blue surface vessels, r _b And (t) is the loss rate of the blue surface vessel. The Lanchester equation shows the loss process of fighting force of two parties in a differential equation mode, the second linear rate shows that the loss rate of the fighting equipment quantity is simultaneously proportional to the product of the loss coefficient of the opponent party of the enemy and the equipment quantity of the two parties, and the specific formula is as follows:

wherein S is _r (t) is the loss coefficient of the red square to the blue square, N _r And (t) the number of anti-ship missiles guided by the space reconnaissance equipment in the red.

The loss rate r of the blue square surface ship can be obtained _b The formula for calculation of (t) is:

r _b (t)＝S _r (t)×N _r (t)×N _b (t)

according to an empirical formula of loss coefficient calculation and in combination with the constructed stock flow model, the calculation formula of the red square to the blue square loss coefficient is obtained as follows:

S _r (t)＝P _{injury by itself} ×P _{Sudden defence} ×P _{Identification} ×V _r (t)×P _{Decision making}

Wherein, P _{Injury by hand} Is the damage probability of the red square anti-ship missile to the blue square target naval vessel after hitting, P _{Sudden defence} Is the penetration probability of a red square anti-ship missile, P _{Identification} Accuracy, V, of identifying targets for Hongfang space reconnaissance equipment _r (t) rate of launching anti-ship missile in reds, P _{Decision making} The accuracy of the decision for the commander is a constant.

The damage probability of the red anti-ship missile is determined by the launching quantity of the red anti-ship missiles, the hit probability of a single missile and the interference probability of a blue party to the red party, and a specific mathematical model is as follows:

wherein, P _{Single-purpose} Hit probability for a red-handed single-shot missile, P _{b-r interference} Interference probability of blue to red, N _{r is lead} The number of the missile is shot for the red anti-ship missile.

The formula for calculating the penetration probability of the red anti-ship missile is as follows:

P _{sudden defence} ＝(1-P _Interception )(1-P _{b-r interference} )

Wherein, P _Interception The interception probability of the blue party to the red party anti-ship missile is obtained.

The interference probability of the blue party to the red party is related to the blue party electronic reconnaissance, the interference equipment processing signal strength and the wave order density of the red party anti-ship missile, and the specific mathematical model is as follows:

wherein, mu _{b scouting} Processing signal strength, mu, for a blue-side electronic reconnaissance device _{b interference} Is the blue-side jammer device processes the signal strength, lambda _r And (4) the density of launching the anti-ship missile for the red square.

The interception probability of a blue party to a red party anti-ship missile is determined by the discovery probability of the blue party to the red party anti-ship missile, the damage probability of the blue party to the red party anti-ship missile and the speed of the blue party to launch the anti-aircraft missile, and the specific mathematical model is as follows:

wherein, P _{Discovery of} Probability of finding target for the blue, P _{b-r damage} Probability of damage to red anti-ship missile for blue square, V _b And (t) is the speed of launching the air-defense missile in the blue.

The speed of the blue-party launched air defense missile depends on the inventory of the blue-party air defense missile and the missile launching time interval, and the specific mathematical model is as follows:

V _b (t)＝(α×N _{warship B} (t)+β×N _{Machine b} (t))×T _b

Wherein alpha and beta are constant terms, the value of alpha depends on the number of missile launching ports of a blue-square surface ship missile, the value of beta depends on the number of carrier-based aircrafts carried by a blue-square aircraft carrier, and N is _{Warship B} 、N _{Machine b} The number of the naval vessels and the carrier-based aircraft, T _b The blue-space missile launch time interval is defined as a multi-pulse function delta (t) in the following formula:

T _b ＝δ(t-nT)

wherein δ (t) is a unit pulse function, and nT is a pulse delay.

And acquiring combat simulation data. The constructed system dynamics model is run with simulation data under dynamic confrontation conditions as input to the performance evaluation model.

And estimating parameters of the model. The invention adopts LISRE (covariance structural model) to estimate the parameters of the structural equation model. Simulation data is used as input for parameter estimation. And generating a covariance matrix of the data, and estimating parameters of the linear measurement model and the nonlinear measurement model by adopting a maximum likelihood method to obtain a corresponding path diagram and estimation values of all parameters.

The basic model after linear SEM standardization of combat effectiveness is shown in fig. 14, the parameter estimation result is shown in fig. 5, fig. 6 is the main goodness-of-fit test statistic, the main statistical indicators all meet the fitting indicator evaluation criteria, and the credibility of the qualitative model can be determined.

After normalization of the non-linear SEM base model, the correlation between the path coefficients and latent variables is shown in FIG. 8. The path coefficients and error terms corresponding to the linear part of the model are consistent with the linear SEM. Figure 7 shows the goodness-of-fit test statistics for a non-linear SEM. The fitting index of the non-linear SEM deteriorates compared to the linear model, but within a reasonable range, the model is still acceptable, i.e., the non-linear SEM can reasonably describe the causal relationship between the intrinsic influencing factors of the combat performance of the space-based information system.

And (5) checking and correcting model parameters. The parameter estimation results need to be corrected if necessary. Common statistics for evaluating model quality include χ ² The statistics, root mean square of approximation error (RMSEA), standard fit index (NFI), comparison fit value number (CFI), goodness of Fit Index (GFI), and the like, which are required to satisfy the evaluation criteria, are shown in fig. 8.

And judging whether the model needs to be corrected or not according to the condition of the goodness of fit test. If the goodness-of-fit inspection effect is good, the constructed combat effectiveness evaluation SEM is fit with the objective reality, otherwise, the constructed structural equation model needs to be corrected from two aspects of a measurement model and a structural model.

And calculating the fighting efficiency of the equipment system. The structural equation model passing the inspection can be used for calculating and evaluating the combat effectiveness of the equipment system. According to the parameter estimation value in FIG. 5, the fighting efficiency of the equipment system (the endogenous latent variable eta and the exogenous latent variables xi 1, xi 2 and xi) ₃ ) The linear analytical model of (1) is:

from the parameter estimation results in fig. 15, the non-linear SEM of operational performance of the equipment system is obtained as follows:

ξ ₁ ＝0.439x ₁ +0.469x ₂ +0.444x ₃ -0.225

ξ ₂ ＝0.676x ₄ +0.568x ₅ -0.207

ξ ₃ ＝0.588x ₆ +0.685x ₇ -0.164

the secondary effect metric model is:

the interaction effect metric model is:

ξ ₁ ξ ₂ ＝1.19x ₁ x ₄ +1.667x ₁ x ₅ +1.111x ₂ x ₄ +0.98x ₂ x ₅ +1.667x ₃ x ₄ +1.389x ₃ x ₅ -0.456

ξ ₁ ξ ₃ ＝0.926x ₁ x ₆ +0.833x ₁ x ₇ +0.192x ₂ x ₆ +2.083x ₂ x ₇ +1.852x ₃ x ₆ +0.298x ₃ x ₇ -0.24

ξ ₂ ξ ₃ ＝2.083x ₄ x ₆ +4.167x ₄ x ₇ +0.833x ₅ x ₆ +1.25x ₅ x ₇ -0.298

as shown in fig. 2, the S103 specifically includes:

s1031, designing a mapping relation of latent variables and explicit variables;

in the step, the mapping relation between the bottom layer indexes in the equipment efficiency evaluation index system and the corresponding latent variables and the corresponding explicit variables of the structural equation model is designed;

s1032, establishing a dynamic model;

in the step, a dynamic model of a basic tree entering system of flow rate reflecting the complex equipment fighting process is established;

s1033, designing a mathematical model of each node;

in the step, a mathematical model of each node is designed;

s1034, obtaining combat simulation data.

In the step, the constructed dynamic model is operated to obtain combat simulation data of different equipment composition schemes.

As shown in fig. 3, the S104 specifically includes:

s1041, establishing a nonlinear structural equation model for the combat ability evaluation;

in the step, a nonlinear structural equation model for evaluating the fighting capacity is established according to the mapping relation between the bottom layer indexes and the latent variables and the apparent variables of the structural equation model;

s1042, converting the aggregation relation into an analysis model;

in the step, the aggregation relation between the efficiency index and the capability index is converted into an analytic model through parameter estimation of the model;

s1043, solving the combat effectiveness of different equipment composition schemes by using an analytical model;

in the step, the operational efficiency of different equipment composition schemes is solved by utilizing an analytical model;

s1044, analyzing the result of the combat effectiveness and giving an evaluation conclusion;

in the step, the result of the operational effectiveness is analyzed, an evaluation conclusion is given, and the equipment compiling scheme with the optimal operational effectiveness is determined.

As shown in fig. 9, a dynamic evaluation system for effectiveness of weaponry systems based on structural equation model includes:

the combat simulation data acquisition module is connected with the scheme generation module and the equipment efficiency evaluation index system and is used for dividing the indexes into exogenous variables X and endogenous variables Y according to the equipment efficiency evaluation index system and whether the factors are determined; dividing the bottom layer index into an exogenous latent variable xi and dividing the secondary index into an endogenous latent variable eta according to whether the index data is directly acquired or not;

the operational effectiveness evaluation module is connected with the operational simulation data acquisition module and used for establishing a linear structural equation model and a nonlinear structural equation model for operational effectiveness evaluation according to the mapping relation among the exogenous significant variable X, the endogenous significant variable Y, the exogenous latent variable xi and the endogenous latent variable eta;

designing a mapping relation between bottom layer indexes in an equipment efficiency evaluation index system and latent variables and apparent variables corresponding to a structural equation model;

designing a mathematical model of each node;

Further, the combat effectiveness evaluation module is further configured to:

establishing a nonlinear structural equation model for evaluating the combat capability according to the mapping relation between the underlying indexes and the latent variables and the apparent variables of the structural equation model;

and analyzing the result of the operational efficiency, giving an evaluation conclusion, and determining an equipment configuration scheme with the optimal operational efficiency.

Example II of the device

An embodiment of the present invention provides a dynamic evaluation apparatus for efficacy of a weaponry system based on a structural equation model, as shown in fig. 16, including: a memory 10, a processor 20 and a computer program stored on the memory 10 and executable on the processor 20, the computer program, when executed by the processor 20, performing the steps as described in the method embodiment as shown in fig. 1.

Example III of the device

An embodiment of the present invention provides a computer-readable storage medium, where a program for implementing information transmission is stored, and when the program is executed by a processor 20, the program implements the steps described in the method embodiment shown in fig. 1.

It should be noted that the embodiment of the storage medium in this specification and the embodiment of the service providing method based on a block chain in this specification are based on the same inventive concept, and therefore specific implementation of this embodiment may refer to implementation of the service providing method based on a block chain described above, and repeated parts are not described again.

The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

In the 30 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as ABEL (Advanced Boolean Expression Language), AHDL (alternate Hardware Description Language), traffic, CUPL (core universal Programming Language), HDCal, jhddl (Java Hardware Description Language), lava, lola, HDL, PALASM, rhyd (Hardware Description Language), and vhigh-Language (Hardware Description Language), which is currently used in most popular applications. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be regarded as a hardware component and the means for performing the various functions included therein may also be regarded as structures within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, apparatuses, modules or units described in the above embodiments may be specifically implemented by a computer chip or an entity, or implemented by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the units may be implemented in the same software and/or hardware or in multiple software and/or hardware when implementing the embodiments of the present description.

One skilled in the art will recognize that one or more embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description 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, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.

The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the description. 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.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both permanent and non-permanent, removable and non-removable media, may implement the information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or apparatus comprising the element.

One or more embodiments of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

All the embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The above description is only an example of the present document and is not intended to limit the present document. Various modifications and changes may occur to those skilled in the art from this document. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of this document shall be included in the scope of the claims of this document.

Claims

1. A dynamic evaluation method for the effectiveness of a weaponry system based on a structural equation model is characterized by specifically comprising the following steps:

s105, respectively carrying out parameter estimation on the linear structure equation model and the nonlinear structure equation model, judging whether the parameter estimation result evaluation index meets the judgment standard, if so, obtaining an analytical model of the effectiveness index, wherein the analytical model is used for solving the combat effectiveness result;

2. The method for dynamically evaluating the effectiveness of a weaponry system based on a structural equation model as claimed in claim 1, wherein S103 comprises:

s1033, designing a mathematical model of each node;

3. The method for dynamically evaluating the effectiveness of a weaponry system based on structural equation models of claim 1, wherein S104 specifically includes:

s1041, establishing a nonlinear structural equation model for evaluating the combat ability according to the mapping relation between the underlying indexes and the latent variables and the apparent variables of the structural equation model;

and S1044, analyzing the result of the operational effectiveness, giving an evaluation conclusion, and determining an equipment compiling scheme with the optimal operational effectiveness.

4. A dynamic evaluation system for effectiveness of weaponry systems based on structural equation models, comprising:

the scheme generation module is used for analyzing the characteristics of the evaluation object and the evaluation requirement to generate a planned space of the equipment fighting scheme, and the planned space comprises a scheme consisting of a plurality of pieces of equipment;

the combat simulation data acquisition module is connected with the scheme generation module and the equipment efficiency evaluation index system and is used for dividing the indexes into an exogenous variable X and an endogenous variable Y according to the equipment efficiency evaluation index system and whether the factors of the equipment efficiency evaluation index system are determined; dividing the bottom layer index into an exogenous latent variable xi and dividing the secondary index into an endogenous latent variable eta according to whether the index data is directly acquired or not;

5. The dynamic weaponry system effectiveness assessment system based on structural equation models of claim 4, wherein the combat simulation data acquisition module is further configured to:

designing a mathematical model of each node;

6. The dynamic weaponry systems effectiveness assessment system based on structural equation models of claim 4, wherein the combat effectiveness assessment module is further configured to:

7. A dynamic evaluation device for the effectiveness of a weaponry system based on a structural equation model is characterized by comprising: memory, processor and computer program stored on the memory and executable on the processor, the computer program, when executed by the processor, implementing the steps of the method for dynamic assessment of weapons systems effectiveness based on structural equation models as claimed in any one of claims 1 to 3.

8. An electronic device, characterized in that the electronic device stores an information transfer implementation program, and the program, when executed by a processor, implements the steps of the method for dynamically evaluating the effectiveness of a weaponry system based on a structural equation model according to any one of claims 1-3.