时间证据融合评估方法考虑时间序列变化的趋势趋势
Sunan Zhang1, Yanxin Gao2, Yuanchao Kou3
1Engineering Training Center, Taiyuan Institute of Technology, Taiyuan, 030008, China. zhangsn@tit.edu.cn.
Scientific reports
|July 11, 2025
概括
这项研究引入了一种新的时间证据融合评估方法. 它通过分析时间序列趋势,有效地处理相互矛盾的数据,减少融合结果的不确定性.
科学领域:
- 信息融合 信息融合
- 人工智能的人工智能
- 数据科学数据科学数据科学
背景情况:
- 由于动态数据,评估时间信息融合具有挑战性.
- 现有的方法可能无法完全捕捉时间对信息融合的影响.
研究的目的:
- 提出一种考虑时间序列趋势的时间证据融合评估方法.
- 增强时间信息和时间因素在聚变中的动态反射.
主要方法:
- 将时间证据序列趋势集成到融合评估中.
- 定义了基于证据变化的命题的时间变化因子.
- 开发了一个结合时间变化因子的证据结合规则.
主要成果:
- 拟议的方法显著增加了联合信念和功能的 (BPA) 值之间的差异.
- 融合结果的相关不确定性显著减少.
- 在处理冲突的时间信息方面表现出能力.
结论:
- 该方法通过结合时间变化趋势,提供了合理的融合评估.
- 它为信息融合评估提供了一种新的方法,考虑时间序列动态.
- 使用连续的定期健康评估数据进行验证.
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