Research on Diagnostic Method Based on Multi-mode Composite Reasoning Mechanism
XI Jin-ju, Wenxue Tan, BI Yu-tong, HE Jin-zhou, Shuhong Li · Jisuanji gongcheng · 2010
【Abstract】The expert system of disease diagnosis is subjected to the bad efficiency, the low accuracy and the lack of contrast, by its only one time use of the field knowledge in a reasoning process, which is built on the base of classical model. Making example of goat, this paper designs the architecture of diagnosis system, and introduces the ideology of multi-mode composite reasoning scheme, constructs both Bayesian reasoning supporting learning by self which is based on probability. The method of measuring semantic is based on pattern recognition, and with different theoretical background. Experimental results show that the composite reasoning scheme enables to improve the utilization rate of knowledge, its accuracy of diagnosis reaches 85%, increasing the contrast, and achieves with an accepted macro effect of diagnosis.