Multi-gun type adaptive AI interactive light weapon training method

By performing time-series regularization and standardization of terminal interaction observation data and resource index data, combined with context separation analysis and gun type adaptation reliability verification, the problems of training session boundary identification and result attribution distortion in multi-person training scenarios are solved, achieving accurate adaptation of training content and reliability of results.

CN122388596APending Publication Date: 2026-07-14HEBEI LIBING TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
HEBEI LIBING TECH CO LTD
Filing Date
2026-05-20
Publication Date
2026-07-14

AI Technical Summary

Technical Problem

Existing digital interactive training systems suffer from several problems in scenarios involving multi-person rotation training and parallel adaptation of multiple types of training objects. These problems include unclear identification of training session boundaries, difficulty in effectively separating previous residual records from the current trainee's training context, unstable matching relationship between training content invocation and step template, and easy confusion between the attribution of interactive prompt records and step submission records. These issues lead to crosstalk in the training process, distorted result attribution, and insufficient traceability of the process trajectory.

Method used

By collecting real-time terminal interaction observation data and resource index data, time-series regularization and standardization preprocessing are performed. Training sessions are established and residual records are isolated based on context separation analysis. Gun type adaptation credibility analysis is performed. Training content and step template binding are verified. Interaction attribution convergence analysis is performed to isolate attribution conflicts. Training results are generated and evidence is archived.

Benefits of technology

It enhances the independence of training sessions, ensures the accuracy of training content and results, solves the problems of content mismatch and insufficient adaptation accuracy during the switching of multiple types of training objects, and improves the controllability of the training process and the reliability of the results.

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Abstract

The application discloses a kind of multi-gun type adaptation AI interactive light weapon training method, it is related to machine learning technical field.This kind of multi-gun type adaptation AI interactive light weapon training method includes: S1, terminal interaction observation data and resource index data are carried out time sequence regulation and standardization preprocessing;S2, according to context separation analysis result carries out training session establishment, residual record isolation and training crosstalk blocking;S3, carries out category verification, content call and step template binding;S4, the terminal interaction observation data of artificial intelligence interaction process is carried out interaction attribution convergence analysis, carries out attribution conflict isolation, interaction record re-inspection and training result track writing;S5, result generation and evidence archiving are carried out.The existing method is usually only executed interface reset or simple initialization in the multi-person training scene, it is difficult to accurately strip the previous residual state and current student training context, prone to training crosstalk and evaluation attribution distortion problem.
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