CD-BFT:基于法典分解的信念函数转化为可能性理论
IEEE transactions on cybernetics
|August 1, 2023
概括
本研究引入了一种新的信念函数转换,以确保可能性质量函数 (PossMFs) 和辅音质量函数的一致组合规则. 新方法保持了可逆性,并改善了信息融合.
科学领域:
- 决策理论 决策理论
- 人工智能的人工智能
- 信息融合 信息融合
背景情况:
- 主观概率质量函数通常由定性可能性质量函数 (PossMFs) 表示.
- 现有的PossMF和和音量函数之间的转换在组合规则中缺乏一致性,阻碍了可逆转换.
研究的目的:
- 提出一种新的信念函数转换方法.
- 为了确保PossMFs和辅音质量函数之间的组合规则的一致性.
- 将转变扩展到可能的信念结构.
主要方法:
- 提出了一个新的信念函数转换,可以通过Smets和Pichon的法典分解来解释.
- 该方法使用组合规则一致性,最小承诺原则和信息融合应用程序进行验证.
主要成果:
- 拟议的转换保持了组合规则的一致性.
- 在PossMFs和辅音质量函数之间实现了可逆性.
- 该转换扩展到可能的信念结构,澄清了可能和证据信息之间的联系.
结论:
- 新型转型解决了现有方法的局限性,使可靠的信息融合成为可能.
- 这项工作为信任函数框架中的可能性信息和证据信息之间的关系提供了新的视角.
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