CN112560213A - System modeling method and system based on model system engineering and hyper-network theory - Google Patents

System modeling method and system based on model system engineering and hyper-network theory Download PDF

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CN112560213A
CN112560213A CN202011530446.7A CN202011530446A CN112560213A CN 112560213 A CN112560213 A CN 112560213A CN 202011530446 A CN202011530446 A CN 202011530446A CN 112560213 A CN112560213 A CN 112560213A
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徐成涛
陈涛
刘俊先
罗爱民
舒振
张晓雪
张萌萌
蔡飞
陈洪辉
罗雪山
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Abstract

The invention belongs to the technical field of system modeling, and discloses a system modeling method and a system based on model system engineering and a super network theory, wherein the system modeling system based on the model system engineering and the super network theory comprises: the system comprises an application scene determining module, an architecture verifying module, an index determining module, a weight determining module, a central control module, an architecture model correcting module, a data collecting module, a data processing module, a data quoting module, an architecture model outputting module and a model converting and outputting module. The method converts the constructed system model group into the hyper-network model, analyzes the system model mapping relation among all the visual angles, combines the generated system hyper-network model group, and finally generates the multi-layer hyper-network model of the system structure, thereby being convenient for quantitatively analyzing the index of the system structure by using a mathematical tool; by top-to-bottom combing and bottom-to-top integration, the integrity and validity of the combed data can be guaranteed.

Description

System modeling method and system based on model system engineering and hyper-network theory
Technical Field
The invention belongs to the technical field of system modeling, and particularly relates to a system modeling method and system based on model system engineering and a hyper-network theory.
Background
At present, the super network theory is a network in a network composed of points, lines and flows, is higher than the existing network based on the existing network, and has the characteristics of complexity, congestion, large scale and the like.
Since the 20 th century, with the increasingly complex application requirements, the system structure is increasingly overstaffed only by the design mode of repeatedly overlapping functions of the system, the reliability and efficiency of the system cannot be effectively guaranteed, and the design thinking based on system engineering is brought forward. The system engineering is a large-scale system combination formed by combining a plurality of systems or complex systems, and the capability on macroscopic dimension is realized by reasonably combining and configuring a group of systems so as to complete the capability which cannot be realized by mechanically stacking the systems. The application scenario of system engineering also covers military, government and commercial fields, such as command, control, communication, computer, intelligence and surveillance and reconnaissance (C4ISR) systems, logistics transportation systems, municipal infrastructure systems, etc. Because the subsystems in the system have the problems of complex topological structure, emerging capability, functional evolution in a macro level and the like, how to effectively establish a model which can comprehensively describe the interaction mechanism in the system from multiple visual angles is an urgent problem to be solved in order to better understand, analyze and design the system.
However, the model established by the existing system modeling method cannot be applied to various scenes, expansibility is not strong, data quantity is large and complex, and meanwhile, the established system model cannot reflect the relation between data and indexes and further cannot perform statistical analysis and processing.
Through the above analysis, the problems and defects of the prior art are as follows: the model established by the existing system modeling method can not be applied to various scenes, has weak expansibility and large and complex data amount, and meanwhile, the established system model can not reflect the relationship between data and indexes and can not be subjected to statistical analysis and processing.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a system modeling method and system based on model system engineering and a hyper-network theory.
The invention is realized in such a way that a system modeling method based on model system engineering and a super network theory comprises the following steps:
determining a specific application scene of a system model through an application scene determining module; based on the determined specific application scene, determining the capability indexes of the application scene which need to be considered and the sub-indexes under each capability index through an architecture determining module;
determining the characteristic values of all sub indexes of the new application scene and the historical application scene, and calculating the distance between all the capacity indexes of the new application scene and the historical application scene according to the characteristic values of all the sub indexes belonging to the same capacity index;
weighting each capacity index distance, obtaining a composite distance between a new application scene and a historical application scene by using a weighted summation method, and determining the similarity between the new application scene and the historical application scene according to the composite distance;
step four, judging whether the capability index of the system structure model corresponding to the historical application scene can meet the requirement of a new application scene: if so, outputting the architecture model; if not, returning to the step two, and recalculating the distance between each capability index of the new application scene and each capability index of the historical application scene;
judging whether the attribute or the number of the determined architecture model corresponding to the historical application scene with the maximum similarity meets the requirement or not by an architecture determining program; carrying out logic verification on the constructed or selected architecture through an architecture verification module;
selecting performance indexes through an index determining module based on the determined application scene and system structure of the system model; dividing all determined performance indexes into a condition attribute set and a decision attribute set through a weight determination module, and establishing a multi-attribute decision matrix;
step seven, respectively normalizing the positive indexes and the negative indexes; calculating the dependence of each condition performance on the decision attribute, and calculating the importance degree of the performance according to the dependence; calculating the weight value of each performance index according to the importance degree;
step eight, the normal operation of each module of the system modeling system based on the model system engineering and the super network theory is coordinately controlled by a central control module through a single chip microcomputer or a controller; verifying and determining the system model after each index weight by using the example data through the system structure model correction module, comparing the system model with the optimal scene of the example data, and correcting the model based on the comparison result;
step nine, determining file information transmitted among the specialties in different fields through a data acquisition module; determining parameters corresponding to file information transmitted among the professional stations; determining a model corresponding to the parameters transferred among the tasks in each post; obtaining product research and development data of system engineering based on the model based on the application scene, the performance index, the file information, the parameter and the model;
analyzing and processing the acquired related data through a data processing module; performing visual display on the processed data through a data reference module, and selecting reference data modeled by the current system; generating a constructed system model based on the corrected system model and the selected reference data through a system model output module; and converting the constructed system model into a super network model through a model conversion output module, and outputting the super network model.
Further, in the first step, the determining, by the architecture determining program, whether the attribute or the number of the architecture model corresponding to the history application scenario with the maximum similarity satisfies a requirement includes:
if the attribute does not meet the requirement, directly checking whether a structure meeting the requirement exists in a structure library: if yes, adding the data into the architecture model and outputting; if not, designing a new architecture model by using a decision tree algorithm;
if the quantity can not meet the requirement, judging whether the directly increased quantity can meet the requirement of the application scene, if so, adding the directly increased quantity into the system structure model, and outputting; if not, a new architecture model is designed using a decision tree algorithm.
Further, in the second step, the calculating the distance between each capability index of the new application scenario and each capability index of the historical application scenario includes:
when the branch indexes are numerical values, calculating the capacity index distance by adopting an Euclidean distance according to the characteristic value of each branch index;
secondly, when the sub-indexes are character types, calculating the capacity index distance by adopting cosine distances according to the characteristic values of the sub-indexes;
thirdly, when the sub-indexes are space constraint, time constraint and force application constraint, the characteristic value of each sub-index adopts Jaccard distance calculation capability index distance.
Further, in step six, the selected indexes as condition attributes include service bandwidth, signal strength, time delay, jitter, and packet loss rate, the decision attribute is a network performance level, and the data matrix D is:
Figure BDA0002851875460000041
wherein each row represents attribute parameter data of a group of PDT networks or B-TrunC networks, and each column represents a conditional attribute, i.e. C ═ { C ═ C1,c2,...,cnDenoted as T ═ c }, decision attributen+1}。
Further, in step nine, the determining, by the data acquisition module, file information transferred among the professionals in different fields includes:
(1) determining a classification framework including at least data and knowledge based on the domain framework;
(2) forming a top-level structure of the database based on the classification framework;
(3) and combing file information transmitted among the specialties under the top layer structure.
Further, in the tenth step, the analyzing and processing the collected related data by the data processing module includes:
(1) establishing reference data used for classifying and sorting each view in the system modeling process through a data processing module;
(2) a view referenceable data list definition module that defines a list of data that each view can refer to.
Further, in the tenth step, the visually displaying the processed data through the data reference module, and selecting the reference data modeled by the current system includes:
(1) according to model data generated during modeling, actual reference data of each view in a defined view reference data list is provided through a real-time reference data matching algorithm;
(2) and displaying the reference data list through a display interface, and selecting the reference data according to the reference data required by modeling and quick dragging of the reference data.
Another object of the present invention is to provide a system modeling system based on model system engineering and super network theory, which applies the system modeling method based on model system engineering and super network theory, the system modeling system based on model system engineering and super network theory comprising:
the application scene determining module is connected with the central control module and used for determining the specific application scene of the system model;
the system structure determining module is connected with the central control module and used for determining and constructing a system model based on an application scene of the system model through a system structure determining program;
the system structure verifying module is connected with the central control module and is used for carrying out logic verification on the constructed or selected system structure;
the index determining module is connected with the central control module and is used for selecting the performance index based on the determined application scene and the system structure of the system model;
the weight determining module is connected with the central control module and is used for determining the weight of each index based on the determined performance index;
the central control module is connected with the application scene determining module, the system structure verifying module, the index determining module, the weight determining module, the system structure model correcting module, the data collecting module, the data processing module, the data quoting module, the system model outputting module and the model conversion outputting module and is used for coordinately controlling the normal operation of each module of the system modeling system based on the model system engineering and the hyper-network theory through a single chip microcomputer or a controller;
the system structure model correction module is connected with the central control module and used for verifying and determining the system model with each index weight by using the example data, comparing the system model with the optimal scene of the example data and correcting the model based on the comparison result;
the data acquisition module is connected with the central control module and is used for acquiring data based on an application scene and performance indexes;
the data processing module is connected with the central control module and is used for analyzing and processing the acquired related data;
the data reference module is connected with the central control module and used for visually displaying the processed data and selecting reference data modeled by the current system;
the system model output module is connected with the central control module and used for generating a constructed system model based on the corrected system model and the selected reference data;
and the model conversion output module is connected with the central control module and is used for converting the constructed system model into a super network model and outputting the super network model.
It is another object of the present invention to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for implementing said model-based systems engineering and hyper network theory architecture modeling method when executed on an electronic device.
It is another object of the present invention to provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method for modeling a model-based system engineering and hyper-network theory architecture.
It is another object of the present invention to provide a computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for implementing said model-based systems engineering and hyper network theory architecture modeling method when executed on an electronic device.
It is another object of the present invention to provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method for modeling a model-based system engineering and hyper-network theory architecture.
By combining all the technical schemes, the invention has the advantages and positive effects that: the system modeling system based on the model system engineering and the hyper-network theory improves the design efficiency during the design of the system structure and saves the design cost; compared with the traditional design process of the architecture model, the architecture model is not directly output according to the mission task, but the most similar architecture model is found out by combining big data drive with the historical architecture model.
Meanwhile, the constructed system model group is converted into the super-network model, the system model mapping relation among all the visual angles is analyzed, the generated system super-network model group is combined, and finally the multi-layer super-network model of the system structure is generated, so that the indexes of the system structure can be conveniently analyzed in a quantitative mode by using a mathematical tool. The method can avoid the problem that data is incomplete and is not systematic due to the fact that the existing model carding is directly started, and can ensure the integrity and the effectiveness of the carded data through top-to-bottom carding and bottom-to-top integration.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a flowchart of a system modeling method based on model system engineering and a hyper-network theory according to an embodiment of the present invention.
FIG. 2 is a schematic structural diagram of a system modeling system based on model system engineering and hyper-network theory according to an embodiment of the present invention;
in the figure: 1. an application scenario determination module; 2. an architecture determination module; 3. an architecture validation module; 4. an index determination module; 5. a weight determination module; 6. a central control module; 7. an architecture model modification module; 8. a data acquisition module; 9. a data processing module; 10. a data reference module; 11. a system model output module; 12. and a model conversion output module.
Fig. 3 is a flowchart of a method for determining and constructing an architectural model based on an application scenario of the architectural model by an architectural determination module according to an embodiment of the present invention.
Fig. 4is a flowchart of a method for determining weights of indexes based on determined performance indexes by a weight determination module according to an embodiment of the present invention.
Fig. 5 is a flowchart of a method for acquiring data based on an application scenario and a performance index by a data acquisition module 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 further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In view of the problems in the prior art, the present invention provides a system modeling method and system based on model system engineering and hyper-network theory, and the present invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the system modeling method based on model system engineering and hyper-network theory provided in the embodiment of the present invention includes the following steps:
s101, determining a specific application scene of a system model through an application scene determining module; determining and constructing a system model based on an application scene of the system model through an architecture determination module;
s102, carrying out logic verification on the constructed or selected architecture through an architecture verification module; selecting performance indexes based on the determined application scene and the system structure of the system model through an index determination module;
s103, determining the weight of each index based on the determined performance index through a weight determining module; the central control module utilizes a single chip microcomputer or a controller to coordinate and control the normal operation of each module of the system modeling system based on the model system engineering and the hyper-network theory;
s104, verifying and determining the system model with each index weight by using the example data through the system structure model correction module, comparing the system model with the optimal scene of the example data, and correcting the model based on the comparison result;
s105, data acquisition is carried out through a data acquisition module based on an application scene and performance indexes; analyzing and processing the acquired related data through a data processing module; performing visual display on the processed data through a data reference module, and selecting reference data modeled by the current system;
s106, generating a constructed system model based on the corrected system model and the selected reference data through a system model output module; and converting the constructed system model into a super network model through a model conversion output module, and outputting the super network model.
In step S105 provided in the embodiment of the present invention, analyzing and processing the acquired related data by the data processing module includes:
(1) establishing reference data used for classifying and sorting each view in the system modeling process through a data processing module;
(2) a view referenceable data list definition module that defines a list of data that each view can refer to.
In step S105 provided in the embodiment of the present invention, the visually displaying the processed data by the data reference module, and selecting reference data modeled by the current system includes:
(1) according to model data generated during modeling, actual reference data of each view in a defined view reference data list is provided through a real-time reference data matching algorithm;
(2) and displaying the reference data list through a display interface, and selecting the reference data according to the reference data required by modeling and quick dragging of the reference data.
As shown in fig. 2, the system modeling system based on model system engineering and hyper-network theory provided in the embodiment of the present invention includes: the system comprises an application scene determining module 1, an architecture determining module 2, an architecture verifying module 3, an index determining module 4, a weight determining module 5, a central control module 6, an architecture model correcting module 7, a data collecting module 8, a data processing module 9, a data reference module 10, an architecture model output module 11 and a model conversion output module 12.
The application scene determining module 1 is connected with the central control module 6 and is used for determining the specific application scene of the system model;
the system structure determining module 2 is connected with the central control module 6 and used for determining and constructing a system model based on an application scene of the system model;
the system structure verification module 3 is connected with the central control module 6 and used for carrying out logic verification on the constructed or selected system structure;
the index determining module 4is connected with the central control module 6 and is used for selecting the performance index based on the determined application scene and the system structure of the system model;
the weight determining module 5 is connected with the central control module 6 and is used for determining the weight of each index based on the determined performance index;
the central control module 6 is connected with the application scene determining module 1, the system structure determining module 2, the system structure verifying module 3, the index determining module 4, the weight determining module 5, the system structure model correcting module 7, the data collecting module 8, the data processing module 9, the data quoting module 10, the system model output module 11 and the model conversion output module 12, and is used for coordinately controlling the normal operation of each module of the system modeling system based on the model system engineering and the super network theory through a single chip microcomputer or a controller;
the system structure model correction module 7 is connected with the central control module 6 and used for verifying and determining the system model with each index weight by using example data, comparing the system model with the optimal scene of the example data and correcting the model based on the comparison result;
the data acquisition module 8 is connected with the central control module 6 and is used for acquiring data based on an application scene and performance indexes;
the data processing module 9 is connected with the central control module 6 and is used for analyzing and processing the acquired related data;
the data reference module 10 is connected with the central control module 6 and used for visually displaying the processed data and selecting reference data modeled by the current system;
the system model output module 11 is connected with the central control module 6 and used for generating a constructed system model based on the corrected system model and the selected reference data;
and the model conversion output module 12 is connected with the central control module 6 and is used for converting the constructed system model into a super network model and outputting the super network model.
The invention is further described with reference to specific examples.
Example 1
The system modeling method based on model system engineering and the hyper-network theory provided by the embodiment of the invention is shown in fig. 1, and as a preferred embodiment, as shown in fig. 3, the method for determining and constructing the system model based on the application scene of the system model by the system structure determination module provided by the embodiment of the invention comprises the following steps:
s201, based on the determined application scene, calculating the similarity between the determined application scene and the application scene of the historical system model, and determining the system structure model corresponding to the historical application scene with the maximum similarity;
s202, judging whether the attribute or the number of the architecture model corresponding to the historical application scene with the maximum similarity meets the requirement.
In step S201 provided in the embodiment of the present invention, based on the determined application scenario, calculating a similarity between the determined application scenario and an application scenario of the historical system model, and determining an architecture model corresponding to the historical application scenario with the largest similarity includes:
(1) based on the determined specific application scene, determining the capability indexes of the application scene which need to be considered and the sub-indexes under each capability index through an architecture determining module;
(2) determining the characteristic values of all sub indexes of a new application scene and a historical application scene, and calculating the distance between each capacity index of the new application scene and each capacity index of the historical application scene according to the characteristic values of all sub indexes belonging to the same capacity index;
(3) weighting each capacity index distance, obtaining a composite distance between a new application scene and a historical application scene by using a weighted summation method, and determining the similarity between the new application scene and the historical application scene according to the composite distance;
(4) judging whether the capability index of the system structure model corresponding to the historical application scene can meet the requirement of a new application scene: if so, outputting the architecture model; and if not, returning to the step (2), and recalculating the distance between the new application scene and each capability index of the historical application scene.
In step (2) provided by the embodiment of the present invention, calculating a distance between each capability index of a new application scenario and each capability index of a historical application scenario includes:
when the branch indexes are numerical values, calculating the capacity index distance by adopting an Euclidean distance according to the characteristic value of each branch index;
secondly, when the sub-indexes are character types, calculating the capacity index distance by adopting cosine distances according to the characteristic values of the sub-indexes;
thirdly, when the sub-indexes are space constraint, time constraint and force application constraint, the characteristic value of each sub-index adopts Jaccard distance calculation capability index distance.
In step S202 provided in the embodiment of the present invention, determining, by an architecture determining program, whether an attribute or a number of an architecture model corresponding to a history application scenario with a maximum similarity satisfies a requirement includes:
if the attribute does not meet the requirement, directly checking whether a structure meeting the requirement exists in a structure library: if yes, adding the data into the architecture model and outputting; if not, designing a new architecture model by using a decision tree algorithm;
if the quantity can not meet the requirement, judging whether the directly increased quantity can meet the requirement of the application scene, if so, adding the directly increased quantity into the system structure model, and outputting; if not, a new architecture model is designed using a decision tree algorithm.
Example 2
The system modeling method based on model system engineering and the hyper-network theory provided by the embodiment of the invention is shown in fig. 1, and as a preferred embodiment, as shown in fig. 4, the method for determining the weight of each index through the weight determination module based on the determined performance index comprises the following steps:
s301, dividing all determined performance indexes into a condition attribute set and a decision attribute set through a weight determination module, and establishing a multi-attribute decision matrix;
s302, respectively normalizing the positive indexes and the negative indexes;
s303, calculating the dependence of each condition performance on the decision attribute, and calculating the importance degree of the performance according to the dependence; and calculating the weight value of each performance index according to the importance degree.
In step S301 provided in the embodiment of the present invention, the selected indexes serving as the condition attributes include a service bandwidth, a signal strength, a time delay, a jitter, and a packet loss rate, the decision attribute is a network performance level, and the data matrix D is:
Figure BDA0002851875460000121
wherein each row represents attribute parameter data of a group of PDT networks or B-TrunC networks, and each column represents a conditional attribute, i.e. C ═ { C ═ C1,c2,...,cnDenoted as T ═ c }, decision attributen+1}。
Example 3
The system modeling method based on model system engineering and the super network theory provided by the embodiment of the invention is shown in fig. 1, and as a preferred embodiment, as shown in fig. 5, the method for performing data acquisition by a data acquisition module based on an application scene and a performance index provided by the embodiment of the invention comprises the following steps:
s401, determining file information transmitted among the specialties in different fields; determining parameters corresponding to file information transmitted among the professional stations;
s402, determining a model corresponding to the parameters transmitted among the tasks in each post;
and S403, obtaining product research and development data of the system engineering based on the model based on the file information, the parameters and the model.
In step S401 provided in the embodiment of the present invention, the determining, by the data acquisition module, file information transferred between specialties in different fields includes:
(1) determining a classification framework including at least data and knowledge based on the domain framework;
(2) forming a top-level structure of the database based on the classification framework;
(3) and combing file information transmitted among the specialties under the top layer structure.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed herein, which is within the spirit and principle of the present invention, should be covered by the present invention.

Claims (10)

1. A system modeling method based on model system engineering and a super network theory is characterized by comprising the following steps:
determining a specific application scene of a system model through an application scene determining module; based on the determined specific application scene, determining the capability indexes of the application scene which need to be considered and the sub-indexes under each capability index through an architecture determining module;
determining the characteristic values of all sub indexes of the new application scene and the historical application scene, and calculating the distance between all the capacity indexes of the new application scene and the historical application scene according to the characteristic values of all the sub indexes belonging to the same capacity index;
weighting each capacity index distance, obtaining a composite distance between a new application scene and a historical application scene by using a weighted summation method, and determining the similarity between the new application scene and the historical application scene according to the composite distance;
step four, judging whether the capability index of the system structure model corresponding to the historical application scene can meet the requirement of a new application scene: if so, outputting the architecture model; if not, returning to the step two, and recalculating the distance between each capability index of the new application scene and each capability index of the historical application scene;
judging whether the attribute or the number of the determined architecture model corresponding to the historical application scene with the maximum similarity meets the requirement or not by an architecture determining program; carrying out logic verification on the constructed or selected architecture through an architecture verification module;
selecting performance indexes through an index determining module based on the determined application scene and system structure of the system model; dividing all determined performance indexes into a condition attribute set and a decision attribute set through a weight determination module, and establishing a multi-attribute decision matrix;
step seven, respectively normalizing the positive indexes and the negative indexes; calculating the dependence of each condition performance on the decision attribute, and calculating the importance degree of the performance according to the dependence; calculating the weight value of each performance index according to the importance degree;
step eight, the normal operation of each module of the system modeling system based on the model system engineering and the super network theory is coordinately controlled by a central control module through a single chip microcomputer or a controller; verifying and determining the system model after each index weight by using the example data through the system structure model correction module, comparing the system model with the optimal scene of the example data, and correcting the model based on the comparison result;
step nine, determining file information transmitted among the specialties in different fields through a data acquisition module; determining parameters corresponding to file information transmitted among the professional stations; determining a model corresponding to the parameters transferred among the tasks in each post; obtaining product research and development data of system engineering based on the model based on the application scene, the performance index, the file information, the parameter and the model;
analyzing and processing the acquired related data through a data processing module; performing visual display on the processed data through a data reference module, and selecting reference data modeled by the current system; generating a constructed system model based on the corrected system model and the selected reference data through a system model output module; and converting the constructed system model into a super network model through a model conversion output module, and outputting the super network model.
2. The model system engineering and hyper-network theory-based system modeling method of claim 1, wherein in the first step, the determining, by the system structure determining program, whether the attribute or the number of the system structure model corresponding to the historical application scenario with the maximum similarity meets the requirement includes:
if the attribute does not meet the requirement, directly checking whether a structure meeting the requirement exists in a structure library: if yes, adding the data into the architecture model and outputting; if not, designing a new architecture model by using a decision tree algorithm;
if the quantity can not meet the requirement, judging whether the directly increased quantity can meet the requirement of the application scene, if so, adding the directly increased quantity into the system structure model, and outputting; if not, a new architecture model is designed using a decision tree algorithm.
3. The model system engineering and hyper-network theory-based system modeling method of claim 1, wherein in the second step, the calculating of the distance between each capability index of the new application scenario and each capability index of the historical application scenario comprises:
when the branch indexes are numerical values, calculating the capacity index distance by adopting an Euclidean distance according to the characteristic value of each branch index;
secondly, when the sub-indexes are character types, calculating the capacity index distance by adopting cosine distances according to the characteristic values of the sub-indexes;
thirdly, when the sub-indexes are space constraint, time constraint and force application constraint, the characteristic value of each sub-index adopts Jaccard distance calculation capability index distance.
4. The model system engineering and super-network theory-based system modeling method according to claim 1, wherein in step six, the selected indexes as condition attributes include service bandwidth, signal strength, time delay, jitter and packet loss rate, the decision attribute is a network performance level, and the data matrix D is:
Figure FDA0002851875450000031
wherein each row represents attribute parameter data of a group of PDT networks or B-TrunC networks, and each column represents a conditional attribute, i.e. C ═ { C ═ C1,c2,...,cnDenoted as T ═ c }, decision attributen+1}。
5. The model system engineering and hyper-network theory-based system modeling method of claim 1, wherein in the ninth step, the determining of the document information transferred between the professions in different fields by the data acquisition module comprises:
(1) determining a classification framework including at least data and knowledge based on the domain framework;
(2) forming a top-level structure of the database based on the classification framework;
(3) and combing file information transmitted among the specialties under the top layer structure.
6. The model system engineering and hyper-network theory-based system modeling method of claim 1, wherein in the tenth step, the analyzing and processing the collected related data through the data processing module comprises:
(1) establishing reference data used for classifying and sorting each view in the system modeling process through a data processing module;
(2) a view referenceable data list definition module that defines a list of data that each view can refer to.
7. The model system engineering and hyper-network theory-based system modeling method of claim 1, wherein in the tenth step, the visually displaying the processed data through the data reference module and selecting the reference data of the current system modeling comprises:
(1) according to model data generated during modeling, actual reference data of each view in a defined view reference data list is provided through a real-time reference data matching algorithm;
(2) and displaying the reference data list through a display interface, and selecting the reference data according to the reference data required by modeling and quick dragging of the reference data.
8. A system modeling system based on model system engineering and super network theory applying the system modeling method based on model system engineering and super network theory according to any one of claims 1 to 7, characterized in that the system modeling system based on model system engineering and super network theory comprises:
the application scene determining module is connected with the central control module and used for determining the specific application scene of the system model;
the system structure determining module is connected with the central control module and used for determining and constructing a system model based on an application scene of the system model through a system structure determining program;
the system structure verifying module is connected with the central control module and is used for carrying out logic verification on the constructed or selected system structure;
the index determining module is connected with the central control module and is used for selecting the performance index based on the determined application scene and the system structure of the system model;
the weight determining module is connected with the central control module and is used for determining the weight of each index based on the determined performance index;
the central control module is connected with the application scene determining module, the system structure verifying module, the index determining module, the weight determining module, the system structure model correcting module, the data collecting module, the data processing module, the data quoting module, the system model outputting module and the model conversion outputting module and is used for coordinating and controlling the normal operation of each module of the system modeling system based on the model system engineering and the hyper-network theory by utilizing a single chip microcomputer or a controller;
the system structure model correction module is connected with the central control module and used for verifying and determining the system model with each index weight by using the example data, comparing the system model with the optimal scene of the example data and correcting the model based on the comparison result;
the data acquisition module is connected with the central control module and is used for acquiring data based on an application scene and performance indexes;
the data processing module is connected with the central control module and is used for analyzing and processing the acquired related data;
the data reference module is connected with the central control module and used for visually displaying the processed data and selecting reference data modeled by the current system;
the system model output module is connected with the central control module and used for generating a constructed system model based on the corrected system model and the selected reference data;
and the model conversion output module is connected with the central control module and is used for converting the constructed system model into a super network model and outputting the super network model.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface for implementing a method for modeling a model based systems engineering and hyper network theory according to any one of claims 1 to 7 when executed on an electronic device.
10. A computer-readable storage medium storing instructions which, when executed on a computer, cause the computer to perform the method of modeling a model-based systems engineering and hyper-network theory architecture according to any one of claims 1 to 7.
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