A Causal Model for Diagnostic Reasoning  

作　　者：彭国强 程虎 

出　　处：《Journal of Computer Science & Technology》2000年第3期287-294,共8页计算机科学技术学报（英文版）

摘　　要：Up to now, there have been many methods for knowledge representation and reasoning in causal networks, but few of them include the research on the coactions of nodes. In practice, ignoring these coactions may influence the accuracy of reasoning and even give rise to incorrect reasoning. In this paper, based on multilayer causal networks, the definitions on coaction nodes are given to construct a new causal network called Coaction Causal Network, which serves to construct a model of neural network for diagnosis followed by fuzzy reasoning, and then the activation rules are given and neural computing methods are used to finish the diagnostic rea soning. These methods are proved in theory and a method of computing the number of solutions for the diagnostic reasoning is given. Finally, the experiments and the conclusions are presellted.Up to now, there have been many methods for knowledge representation and reasoning in causal networks, but few of them include the research on the coactions of nodes. In practice, ignoring these coactions may influence the accuracy of reasoning and even give rise to incorrect reasoning. In this paper, based on multilayer causal networks, the definitions on coaction nodes are given to construct a new causal network called Coaction Causal Network, which serves to construct a model of neural network for diagnosis followed by fuzzy reasoning, and then the activation rules are given and neural computing methods are used to finish the diagnostic rea soning. These methods are proved in theory and a method of computing the number of solutions for the diagnostic reasoning is given. Finally, the experiments and the conclusions are presellted.

关 键 词：coaction node coaction causal network neural network fuzzy reasoning diagnostic reasoning causal network 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]