Cluster algorithm training evolution system and method based on architecture model definition

Through the cluster algorithm training evolution system based on the architecture model, the problem of inexplicable simulation results and insufficient scalability in the coordinated combat of multiple arms is solved, and efficient and traceable cluster decision-making and simulation evaluation are achieved to adapt to changes in equipment and requirements.

CN120278227AActive Publication Date: 2025-07-08YITONG XINGYUN (BEIJING) TECH DEV CO LTD
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Patent Information

Application Number
CN202510758668.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-06-09
Publication Date
2025-07-08
Estimated Expiration
2045-06-09

AI Technical Summary

Technical Problem

The existing technology lacks unified system standards in the coordinated combat of multiple arms and multi-weapon systems, which makes it difficult for simulation deduction results to be interpretable and credible, and traditional methods are difficult to quickly adapt to changes in equipment or requirements, and lack of system scalability and traceability.

Method used

The cluster algorithm is used to train the evolution system based on the architecture model definition, including data acquisition, architecture, algorithm training, simulation evaluation and result output units. The task resources and goals are uniformly defined through the architecture model, deep reinforcement learning is used to optimize the cluster decision strategy, and the model is optimized through self-verification and closed-loop feedback mechanisms.

Benefits of technology

It realizes compatibility and scalability between different task resources, improves system decision-making efficiency and traceability, reduces the difficulty of adjustment in system upgrades and scenario switching, and ensures the accuracy and credibility of simulation results.

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Abstract

The invention discloses a cluster algorithm training evolution system and method based on system architecture model definition. A data acquisition unit acquires task targets and task resources; the system architecture unit analyzes task resources according to a task target and outputs a system architecture model; the algorithm training unit carries out algorithm training according to the system architecture model and outputs a cluster decision strategy and a task allocation scheme; the simulation evaluation unit performs simulation deduction on the cluster decision strategy, evaluates the effect of the task allocation scheme and outputs a corresponding evaluation report; and the result output unit outputs the evaluation report. According to the method, firstly, functions and interfaces of various task resources are defined in a unified mode through the system architecture model, compatibility, expansibility and interoperability among different task resources can be ensured, secondly, the system architecture model and the cluster decision algorithm are combined, decision efficiency is optimized, and traceability and transparency are improved.
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