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In order to comprehensively assess the effectiveness of the defense equipment system, both the system’s composition and the impact of camouflage equipment were considered. The key factors influencing the system’s effectiveness were meticulously analyzed in a hierarchical manner. Based on the principles of Bayesian networks, a comprehensive effectiveness evaluation model was developed. The structure and parameters of this model were optimized using an improved K2 algorithm and Bayesian estimation techniques. The model’s validity was subsequently verified through a case study, which underscored the crucial role of camouflage equipment in enhancing the comprehensive effectiveness of the system. Specific recommendations were proposed to improve the effectiveness of camouflage equipment, thereby providing valuable insights for the development and tactical development of camouflage equipment on future battlefields.

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Research on the Effectiveness Evaluation of Defence Equipment System Based on Bayesian Network

  • 会议论文

  • 发表日期：

    2026年

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  • Wennan Yuan,
  • Xiaojun Wang,
  • Jian Li,
  • Ying Mi,
  • Weiwei Bian,
  • Xinghao Li

摘要

In order to comprehensively assess the effectiveness of the defense equipment system, both the system’s composition and the impact of camouflage equipment were considered. The key factors influencing the system’s effectiveness were meticulously analyzed in a hierarchical manner. Based on the principles of Bayesian networks, a comprehensive effectiveness evaluation model was developed. The structure and parameters of this model were optimized using an improved K2 algorithm and Bayesian estimation techniques. The model’s validity was subsequently verified through a case study, which underscored the crucial role of camouflage equipment in enhancing the comprehensive effectiveness of the system. Specific recommendations were proposed to improve the effectiveness of camouflage equipment, thereby providing valuable insights for the development and tactical development of camouflage equipment on future battlefields.