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Fault Diagnosis Knowledge Base Optimization Based on Decision Tree

This paper proposed a new method of fault diagnosis knowledge base optimization based on decision tree algorithm. Firstly, the fault tree of drawn on the Visio platform generated decision table was used as training dataset. Then, the decision tree was generated by methods of the decision tree algorithm. Finally, the decision rule base was generated from the decision tree. The comparison experiments of optimized and non-optimized show that this method can reduce the number of circulation, contradiction and redundant rules of knowledge base, and shorten the time of fault diagnosis.