计算机科学 ›› 2011, Vol. 38 ›› Issue (10): 23-28.

• 综述 • 上一篇    下一篇

模糊认知图研究进展

马楠 杨炳儒 鲍泓 郭建威   

  1. (北京科技大学计算机与通信工程学院 北京100083);(北京联合大学信息学 院 北京100101)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家自然科学基金(60675030,60875029),北京市属高等学校人才强教计划资助项目PAR(IHLB)资助。

Research on Progress of Fuzzy Cognitive Map

MA Nan,YANG Bing-ru,BA0 Hong,GUO Jian-wei   

  • Online:2018-11-16 Published:2018-11-16

摘要: 模糊认知图(Fuzzy Cognitive Map, FCM)作为知识表示、推理和软计算方法,通过在传统认知图模型中引入模糊测度来量化概念(concept)间因果关系的影响程度,近年来已成为国内外的研究热点。从研究进展的视角,归纳了FCM的基本框架和推理机制,总结了主流研究中FCM的基本类型,分析了FCM学习算法的主要特征,提出了今后专题研究方向的基本设想,以期对后续研究有所助益。

关键词: 模糊认知图,因果关系,推理机制,学习方法

Abstract: As an effective tool for knowledge representation reasoning and soft computing method, fuzzy cognitive map (FCM) has become a hot issue for researchers home and abroad in recent years. FCM quantifies the causal relationship between concepts. We summarized the basic framework and reasoning mechanism of FCM from the perspective of research development, generalized classification of FCM in the mainstream research and analyzed main features of its learning algorithm and put forward possibilities of future research, expecting to be helpful to the future research.

Key words: Fuzzy cognitive map, Causal relationship, Reasoning mechanism, Learning algorithm

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