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    Abstract:

    In this paper, a structural design of the knowledge network for the identification and classification fault diagnosis model is introduced together with the detailed reasoning algorithm and fault diagnosis algorithm. Reasoning with uncertainty is realized through the message propagation among the nodes, which makes it have the characteristic of a distributed system. In addition, the machine learning algorithm for the judgement function is also presented. This algorithm adopts the package wrapping algorithm to select the border points sets, which makes the speed of curve approach more quickly.

    Reference
    1  Luca Console, Claudio Borlo, Alberto casale et al. Dealing with uncertainty in a distributed expert system architecture. In: Bouchon-Meunier B, Yager P R, Zadeh LA eds. Proceedings of the 3rd International Conference'90 on Information Processing and Management of Uncertainty in Knowledge-based Systems. Berlin Heidelberg: Springer-Verlag, 1990. 568~577 2  Hayes J E, Michie D, Mikulich L I. Theory of approximate reasoning. Machine Intelligence, 1989,9(2):149~194 3  张立明.人工神经网络的模型及其应用.上海:复旦大学出版社,1992. (Zhang Li-ming. The Model of Artificial Neural Network and It's Application. Shanghai: Fudan University Press, 1992) 4  徐利治等.函数逼近的理论与方法.上海:上海科学技术出版社,1983. (Xu Li-zhi et al. The Theories and Methods of Function Approach. Shanghai: Shanghai Science and Technology Press, 1983)
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黄 波,倪重匡,高丽萍.故障诊断专家系统的知识网络设计.软件学报,1998,9(7):554-560

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History
  • Received:March 15,1997
  • Revised:June 26,1997
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