Simulation experiment data integration and visual analysis method and system
By preprocessing military simulation experimental data and Fp-Growth algorithm analysis, FP trees are built and association rules are generated, which solves the problem of low data integration and analysis efficiency in traditional methods, and realizes efficient data management and in-depth analysis, providing intuitive user interface and auxiliary decision-making support.
Patent Information
- Application Number
- CN202411857117.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-17
- Publication Date
- 2025-04-11
AI Technical Summary
When traditional methods process and visually analyze military simulation experimental data, there are problems such as difficult data integration, low analysis efficiency and poor visualization effect, which is difficult to meet the needs of military personnel for rapid and accurate data analysis.
A simulation experimental data integration and visual analysis method is adopted, and the military simulation experimental data is read for preprocessing and classified storage. The FP tree is built using the Fp-Growth algorithm, frequent item sets are generated and association rules are obtained, and the data is finally visualized and presented.
It realizes efficient data management and in-depth analysis, provides an intuitive user interface and auxiliary decision-making support, and improves user experience and data mining efficiency.
Smart Images
Figure CN119808376A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of computer technology, and more specifically to a simulation experiment data integration and visualization analysis method and system. Background Art
[0002] At present, the processing and visualization analysis of military simulation experiment data plays an indispensable role in modern military training and research. With the development of military technology, the amount of data generated by military simulation experiments has grown exponentially. These data contain a large amount of important information such as tactics, technical information, and combat effectiveness evaluation results. However, traditional methods are powerless in the face of such a large amount of data. There are problems such as difficulty in data integration, low analysis efficiency, and poor visualization effects. It is difficult to meet the needs of military personnel for fast and accurate data analysis, resulting in the value of experimental data not being fully explored. Therefore, how to efficiently manage and analyze military simulation experiment data and provide intuitive and in-depth data insights is an urgent problem that technicians in this field need to solve. Summary of the invention
[0003] In view of this, the present invention provides a simulation experiment data integration and visualization analysis method and system to overcome the above-mentioned defects.
[0004] In order to achieve the above object, the present invention adopts the following technical solution:
[0005] A simulation experiment data integration and visualization analysis method, the specific steps are:
[0006] The processing steps of the first subsystem are:
[0007] Reading military simulation experiment data, preprocessing the military simulation experiment data, and classifying and storing the data in a preset database;
[0008] The processing steps of the second subsystem are:
[0009] Extracting the military simulation experiment data from the database based on the request instruction, and caching the military simulation experiment data in a preset format;
[0010] Processing the military simulation experiment data based on the Fp-Growth algorithm to construct an FP tree, generate frequent item sets, and obtain association rules that meet the confidence level;
[0011] Based on the association rules, any military simulation experiment data is analyzed to obtain analysis results, and the analysis results are visualized.
[0012] Optionally, the preset database is the DAMO database.
[0013] Optionally, the step of reading the military simulation experiment data is:
[0014] Constructing a data table in the preset database based on the military simulation experiment data;
[0015] The first subsystem obtains the military simulation experiment data based on the data table.
[0016] Optionally, the request instruction is an axios request.
[0017] Optionally, the steps of constructing the FP tree are:
[0018] Based on the cached military simulation experiment data, all items are extracted using the Fp-Growth algorithm and an item header table is constructed, wherein each item in the item header table is sorted based on a preset rule;
[0019] Sorting the cached military simulation experiment data according to the order of each item in the item header table to construct a data set;
[0020] Building an initial PF tree based on the data set, wherein any node of the initial PF tree includes an item ID and a count value;
[0021] The initial PF tree is traversed to obtain frequent item sets, the items are screened based on the relationship between the frequent item sets and a preset minimum support, and the FP tree is constructed.
[0022] Optionally, the association rules are obtained recursively.
[0023] A simulation experiment data integration and visualization analysis method and system, including: a simulation data subsystem, a service subsystem and a database;
[0024] The simulation data subsystem is used to read the military simulation experiment data, and pre-process and classify and store the military simulation experiment data;
[0025] The database is used to store the pre-processed military simulation experiment data into a preset database;
[0026] The service subsystem is used to process and integrate the military simulation experiment data in the database, and supports data operation and visual display.
[0027] Optionally, the service subsystem is constructed using Vue framework and HTML
[0028] It can be seen from the above technical solutions that the present invention provides a simulation experiment data integration and visualization analysis method and system, which has the following beneficial effects compared with the prior art:
[0029] Enhanced data management capabilities: The present invention uses data integration technology to effectively collect and organize military simulation experiment data from different sources and formats, ensuring the consistency and integrity of the data;
[0030] Intuitive user interface: The front-end application developed using the Vue framework provides a friendly and intuitive user interface, allowing non-technical personnel to easily understand and operate complex military simulation experiment data, greatly improving the user experience;
[0031] Deep data analysis: The introduction of the Fp-Growth algorithm for association rule mining can discover hidden patterns and trends from a large amount of experimental data, helping military decision-makers to formulate more scientific and reasonable strategies;
[0032] Auxiliary decision support: Through comprehensive analysis of simulation experiment data, the present invention can provide powerful data support for military strategic planning and tactical exercises, and assist commanders in making optimal decisions.
[0033] Strong scalability: The present invention has good scalability and is easy to integrate new technologies and functional modules. BRIEF DESCRIPTION OF THE DRAWINGS
[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.
[0035] Figure 1 A schematic diagram of the method provided by the present invention;
[0036] Figure 2 A schematic diagram of the experimental damage probability analysis provided by the present invention;
[0037] Figure 3 This is a schematic diagram of the system structure provided by the present invention. DETAILED DESCRIPTION
[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0039] The embodiment of the present invention discloses a simulation experiment data integration and visualization analysis method, such as Figure 1 As shown, the specific steps are:
[0040] The processing steps of the first subsystem are:
[0041] Read military simulation experiment data, pre-process the military simulation experiment data, and classify and store them in a preset database;
[0042] The processing steps of the second subsystem are:
[0043] Extracting military simulation experiment data from a database based on a request instruction, and caching the military simulation experiment data in a pre-set format;
[0044] Based on the Fp-Growth algorithm, the military simulation experiment data is processed to construct the FP tree, generate frequent item sets, and obtain association rules that meet the confidence level;
[0045] Based on association rules, any military simulation experiment data is analyzed to obtain analysis results, which are then visualized.
[0046] In one embodiment, the preset database is the DAMO database.
[0047] In one embodiment, the steps of reading military simulation experiment data are:
[0048] Construct a data table based on military simulation experiment data in a preset database;
[0049] The first subsystem obtains military simulation experiment data based on a data table.
[0050] Furthermore, all the required Excel files are constructed in the DAMO database based on the military simulation experiment data; the military simulation data subsystem reads the Excel files with military simulation experiment data through file upload, and performs data preprocessing operations (cleaning, screening, etc.), and stores all military simulation experiment data of each unit in the DAMO database.
[0051] In one embodiment, the request instruction is an axios request.
[0052] In one embodiment, the steps of constructing the FP tree are:
[0053] Furthermore, when the Fp-Growth algorithm is used to process (mine) data, the data set is first scanned (the data set is constructed based on cached military simulation experiment data), all data is stored in an item header table, and sorted from high to low according to the frequency of occurrence; then the data set is re-sorted according to the order in the item header table, and all items of a transaction are arranged according to the order in the item header table to construct a new data set, and the items that do not meet the minimum support are deleted; based on the new data set, an FP tree is constructed, and the node includes an item ID and a count value. Each piece of data is inserted into the tree according to the order in the item header table. If the item already exists, the count value of the corresponding node is increased by 1, otherwise a new node is created and the count value is 1. After the FP tree is constructed, frequent item sets can be found by traversing the tree. Specifically, starting from the leaf node and traversing upward to the root node, each traversal path forms a frequent item set. The proportion of frequent item sets in the entire data set is the support. If the set of nodes on the path and its descendant nodes is greater than or equal to the minimum support, then the frequent item set corresponding to the path meets the requirements. Finally, all frequent items can be directly obtained through the frequent pattern tree. If the association rules between them need to be further mined, it can be completed in a recursive way. Specifically, select an item from a frequent item set as the antecedent, and then filter the association rules that meet the requirements according to the confidence. The association rules between massive military simulation experiment data, such as the number of warheads and the damage area, can be obtained, and then the laws in the massive military simulation experiment data can be further intuitively analyzed.
[0054] Furthermore, by using axios request, Spring Boot+Vue3 framework finally forms front-end and back-end separation, and uses Fp-Growth algorithm to mine and process data, so as to realize the visual analysis of military simulation experiment teaching data by browser. The simulation results are as follows: Figure 2 As shown, the x-axis represents the number of warheads and the y-axis represents the damage probability. Therefore, it can be concluded that in military simulation experiments, the damage probability increases with the increase in the number of warheads in nuclear bomb damage experiments.
[0055] In this embodiment, the Web service subsystem uses the JDBC driver to connect the back end with the DAMO database, and realizes the data access interface connection between the front and back ends; the Web service subsystem obtains the data source of each unit through axios requests and integrates them into the Web service, realizing data transmission between the front and back ends.
[0056] This embodiment also discloses a simulation experiment data integration and visualization analysis system, which implements integration and visualization analysis based on the Fp-growth algorithm + Spring Boot + Vue3 framework. Figure 3 As shown, it includes: simulation data subsystem, service subsystem and database;
[0057] The simulation data subsystem is used to read the military simulation experiment data, and to pre-process and classify and store the military simulation experiment data;
[0058] A database, used to store the pre-processed military simulation experiment data into a preset database;
[0059] The service subsystem is used to process and integrate the military simulation experiment data in the database, and supports data operation and visualization.
[0060] Furthermore, the system uses Spring Boot+Vue3 as the basic framework and uses the DAMO database. The system is divided into two parts: the military simulation data subsystem and the Web service subsystem. The military simulation data subsystem first reads the military simulation experiment data, then performs data preprocessing (cleaning, screening) and other operations, and finally stores all military simulation experiment data in the DAMO database.
[0061] In the Web service subsystem, the relevant military simulation experiment information data is first extracted from the database through axios requests, and then the data is converted and stored in the Web server in json format or other forms. Finally, the experimenters can use the Web service to extract the relevant military simulation experiment information data and use the Vue framework to perform data operations (query, add, delete, modify) and visual interface display; the Web service subsystem is also responsible for receiving data from the military simulation data subsystem and processing and integrating it through data cleaning, classification and other operations, thereby realizing military simulation experiment data integration and visual analysis.
[0062] In one embodiment, the service subsystem is constructed using the Vue framework and HTML.
[0063] Furthermore, Vue framework + HTML is used to process and visualize the simulation experiment data, and IDEA is used as the programming tool.
[0064] In this embodiment, the front end can cache the resources of the page locally by using the Application Cache API provided by HTML, so that users can access the page even without a network connection; or by using ServiceWorker, the resources of the page can be cached locally, which improves the access speed of the page and the user experience, and reduces the number of requests to the back end. The back end can control the caching strategy of static resources and API responses through HTTP cache headers to improve system performance.
[0065] In one embodiment, in order to improve the maintainability and consistency of the code, a code reuse method is adopted, specifically: defining one or more abstract base classes, which contain common properties and methods applicable to all types of file processing;
[0066] Subclasses inherit from abstract base classes and implement specific behaviors based on specific needs;
[0067] Apply the principle of polymorphism so that different subclasses can change their behavior independently without affecting other components;
[0068] Implement a modular development strategy to create highly cohesive components through inheritance and composition;
[0069] Use dependency injection techniques to increase system flexibility and testability;
[0070] Follow the interface isolation principle, reduce unnecessary interface dependencies, and improve code quality;
[0071] Provides detailed documentation and comments to ensure that the code is easy to understand and maintain.
[0072] Furthermore, by defining an abstract base class that contains common properties and method implementations, subclasses can reuse these codes through inheritance. For example, in the back-end military simulation data subsystem, it is necessary to extract data from Excel files to process file uploads. In this case, a subclass can be created to inherit the parent class used for file processing, and finally the file upload function is implemented. The same is true for other aspects, such as form validation, data processing, etc., which reduces duplicate code and improves code maintainability and consistency.
[0073] In one embodiment, the front-end and back-end can jointly use TypeScript to ensure that the data types of interface calls are consistent, thereby reducing errors in data transmission and improving development quality.
[0074] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.
[0075] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A simulation experiment data integration and visualization analysis method, characterized in that: The specific steps are: The processing steps of the first subsystem are: Reading military simulation experiment data, preprocessing the military simulation experiment data, and classifying and storing the data in a preset database; The processing steps of the second subsystem are: Extracting the military simulation experiment data from the database based on the request instruction, and caching the military simulation experiment data in a preset format; Processing the military simulation experiment data based on the Fp-Growth algorithm to construct an FP tree, generate frequent item sets, and obtain association rules that meet the confidence level; Based on the association rules, any military simulation experiment data is analyzed to obtain analysis results, and the analysis results are visualized.
2. A simulation experiment data integration and visualization analysis method according to claim 1, characterized in that: The default database is the DAMO database.
3. A simulation experiment data integration and visualization analysis method according to claim 1, characterized in that: The steps of reading the military simulation experiment data are as follows: Constructing a data table in the preset database based on the military simulation experiment data; The first subsystem obtains the military simulation experiment data based on the data table.
4. A simulation experiment data integration and visualization analysis method according to claim 1, characterized in that: The request instruction is an axios request.
5. A simulation experiment data integration and visualization analysis method according to claim 1, characterized in that: The steps of constructing the FP tree are: Based on the cached military simulation experiment data, all items are extracted using the Fp-Growth algorithm and an item header table is constructed, wherein each item in the item header table is sorted based on a preset rule; Sorting the cached military simulation experiment data according to the order of each item in the item header table to construct a data set; Building an initial PF tree based on the data set, wherein any node of the initial PF tree includes an item ID and a count value; The initial PF tree is traversed to obtain frequent item sets, the items are screened based on the relationship between the frequent item sets and a preset minimum support, and the FP tree is constructed.
6. A simulation experiment data integration and visualization analysis method according to claim 1, characterized in that: The association rules are obtained recursively.
7. A simulation experiment data integration and visualization analysis method and system, characterized in that: include: Simulate data subsystem, service subsystem and database; The simulation data subsystem is used to read the military simulation experiment data, and pre-process and classify and store the military simulation experiment data; The database is used to store the pre-processed military simulation experiment data into a preset database; The service subsystem is used to process and integrate the military simulation experiment data in the database, and supports data operation and visual display.
8. A simulation experiment data integration and visualization analysis method and system according to claim 7, characterized in that: The service subsystem is constructed using the Vue framework and HTML.