Uncertainty Reasoning With Weight And Its Application In Expert System Of ECG Diagnose

Electrocardiogram (ECG) is one of the necessary instruments used for clinic heart disease diagnosing. Researching and developing ECG auto- recognizing system can avoid most defects brought by reading ECG manually. It can also improve the accurate ratio of heart disease diagnosing. This system has important social significance and applied worthiness.This paper develops an expert system for Electrocardiogram diagnosis. Its uncertainty reasoning with weight is based on the experience and specialty knowledge of experts. First, the knowledge of ECG diagnosing is summarized; second it studies the traditional methods for uncertainty inference and presents an uncertainty reasoning with weight. The new method has powerful agglomerate ability and has much more rationality. At last, an expert system for Electrocardiogram diagnosis is developed and details about fuzzy rules, knowledge representation, uncertainty inference implementation and the structure of knowledge database are put forward. The efficiency of the system is showed in practical application.