计算机应用 ›› 2019, Vol. 39 ›› Issue (6): 1626-1631.DOI: 10.11772/j.issn.1001-9081.2018102218

• 人工智能 • 上一篇    下一篇

考虑决策者时序偏好的时域证据融合方法

李旭峰1, 宋亚飞2, 李晓楠3   

  1. 1. 中国农业银行软件开发中心 成都研发部, 成都 610015;
    2. 空军工程大学 防空反导学院, 西安 710051;
    3. 南通大学 商学院, 江苏 南通 226019
  • 收稿日期:2018-11-05 修回日期:2019-01-18 出版日期:2019-06-10 发布日期:2019-06-17
  • 通讯作者: 宋亚飞
  • 作者简介:李旭峰(1990-),男,河南汝州人,助理工程师,硕士,主要研究方向:网络通信、系统仿真;宋亚飞(1988-),男,河南汝州人,讲师,博士,CCF会员,主要研究方向:智能推理与决策;李晓楠(1987-),女,河南汝州人,副教授,博士,主要研究方向:营销决策。
  • 基金资助:
    国家自然科学基金资助项目(61703426);中国博士后基金资助项目(2018M633680)。

Temporal evidence fusion method with consideration of time sequence preference of decision maker

LI Xufeng1, SONG Yafei2, LI Xiaonan3   

  1. 1. Chengdu R & D Department, Software Development Center of Agricultural Bank of China, Chengdu Sichuan 610015, China;
    2. College of Air and Missile Defense, Air Force Engineering University, Xi'an Shaanxi 710051, China;
    3. School of Business, Nantong University, Nantong Jiangsu 226019, China
  • Received:2018-11-05 Revised:2019-01-18 Online:2019-06-10 Published:2019-06-17
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61703426), the China Postdoctoral Science Foundation (2018M633680).

摘要: 针对时域不确定信息的融合难题,为充分体现时域信息融合的动态性特点和时间因素对融合的影响,在证据理论的基础上,提出一种考虑决策者时序偏好的时域证据融合方法。首先将决策者对时序的偏好融入时域证据融合,通过分析时域证据序列的特点,在定义时序记忆因子的基础上,对决策者的时序偏好进行度量;然后通过构建优化模型求解时序权重,再结合证据信任度的概念,对证据源进行修正;最后利用Dempster组合规则对修正后的证据进行融合。数值算例表明,与没有考虑时间因素的融合方法相比,考虑决策者时序偏好的证据融合方法可以有效处理时域信息序列中的冲突信息,得到合理的融合结果;同时,所提方法充分考虑了时域证据序列的信任度和决策者的主观偏好,可以反映决策者主观因素对时域证据融合的影响,较好地体现了时域证据融合的动态性特点。

关键词: 证据理论, 时序偏好, 时序权重, 证据信任度, 证据融合

Abstract: Aiming at temporal uncertain information fusion problem, to fully reflect the dynamic characteristic and the influence of time factor on temporal information fusion, a temporal evidence fusion method was proposed with considering decision maker's preference for time sequence based on evidence theory. Firstly, time sequence preference of decision maker was fused to temporal evidence fusion, through the analysis of characteristics of temporal evidence sequence, decision maker's preference for time sequence was measured based on the definition of temporal memory factor. Then, the evidence source was revised by time sequence weight vector obtained by constructing the optimal model and evidence credibility idea. Finally, the revised evidences were fused by Dempster combination rule. Numerical examples show that compared with other fusion methods without considering time factor, the proposed method can deal with conflicting information in temporal information sequence effectively and obtain a reasonable fusion effect; meanwhile, with the consideration of the credibility of temporal evidence sequence and the subjective preference of decision maker, the proposed method can reflect the influence of subjective factors of decision maker on temporal evidence fusion, giving a good expression to the dynamic characteristic of temporal evidence fusion.

Key words: evidence theory, time sequence preference, time sequence weight, evidence credibility, evidence fusion

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