研究武器指标系统的构建和智能评估方法的研究
Shuai Wang1,2, Yuhong Du3,4, Shuaijie Zhao1,2
1School of Mechanical Engineering, Tiangong University, 399 Bin Shui West Road, Xiqing District, Tianjin, 300387, China.
Scientific reports
|November 8, 2023
概括
本研究介绍了一个智能武器和设备索引系统,使用测试视频检测目标. 新方法提高了战斗有效性评估的效率和稳定性,改善了数据评估.
科学领域:
- 工程 工程师 工程师 工程师
- 计算机科学 计算机科学
- 防务技术 防务技术 技术
背景情况:
- 传统的武器和装备索引系统受到主观干扰和低施工效率的影响.
- 设备测试视频数据为客观和有效的评估提供了丰富的来源.
研究的目的:
- 在设备测试视频数据上使用目标检测开发智能索引系统构建和评估方法.
- 为了提高武器系统战斗有效性评估的效率,客观性和稳定性.
主要方法:
- 开发了一个优化的IPSO-BP网络模型,具有动态权重和自适应性学习因素.
- 提出了一种改进的DS (Dempster-Shafer) 证据平行神经网络评估方法,提高了数值稳定性.
- 使用改进的剩余网络块构建了一个基于多视图的综合CNN (卷积神经网络) 功能集成评估模型.
主要成果:
- 提出的方法证明了指标系统的高效和智能构建.
- 与现有方法相比,智能评估方法显示出更好的稳定性和准确性.
- 该研究通过先进的计算技术成功丰富了指标数据的评估.
结论:
- 基于目标检测的方法显著减少了对索引系统构建的主观干扰.
- 开发的智能评估模型为评估武器和装备战斗效率提供了更稳定,更有效的替代方案.
- 这项研究为通过人工智能和机器学习推进国防技术评估提供了有价值的框架.
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