• CN:11-2187/TH
  • ISSN:0577-6686

›› 2005, Vol. 41 ›› Issue (5): 98-103.

• 论文 • 上一篇    下一篇

智能化系统的知识表达与推理机制

伍奎;李润方;刘景浩   

  1. 重庆大学机械传动国家重点实验室
  • 发布日期:2005-05-15

KNOWLEDGE EXPRESS AND INTEGRATED REASONING MECHANISM IN INTELLIGENT SYSTEM

Wu Kui;Li Runfang;Liu Jinghao   

  1. State Key Laboratory of Mechanical Transmission, Chongqing University
  • Published:2005-05-15

摘要: 针对智能化系统知识研究中的知识表达、学习,提出基于神经网络、模糊逻辑、专家规则结合的图形化拓扑网络结构知识表达及相应的学习方法,能灵活地表达对象知识,方便、直观地形成知识库,有利于智能化系统的知识学习;根据智能化推理中常用的专家系统、模糊逻辑、神经网络等推理的互补性,结合图形化拓扑网络结构知识表达的通用知识库,提出融合型推理模型,能形成较强的推理功能,有效地应用和处理智能化系统知识。实际应用于设备状态监测诊断取得了令人满意的效果。

关键词: 监测诊断, 模糊逻辑, 神经网络, 智能化, 专家系统

Abstract: For knowledge express and learning, A novel conception of graphical topological network knowledge express ba-sed on neural network and fuzz logic rules and relativeknowled-ge learning method are put forward. It can express knowledge neatly, form knowledge warehouse conveniently and straight, make for learn from intelligent system. Based on the reciprocity of expert system, fuzz logic and neural network etc. in common use in intelligent reasoning, and combined general knowledge pool of graphical topological network knowledge express, the integrated reasoning model are brought forward, it can form better reasoning function, apply and deal with intelligent system availably. This achieved in practice of device status monitoring and diagnosis.

Key words: Expert system, Fuzz logic, Intelligent system, Monitoring and diagnosis, Neural network

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