Expert system of goat disease diagnosis with dual-reasoning-kernel

Expert Systems have been widely used in the field of diagnosis of animal diseases and crop pests. For the purpose of helping the local veterinaries to diagnose goat disease, authors constructed expert system and proposed dual-core diagnosis mechanism of inference engine, which is the credibility factor associated with the weighted forecast reasoning and machine learning Bayesian which supports reasoning algorithms, The prototype system was constructed, and some field experiments were carried out. Experimental results showed that in contrast to the traditional-single reasoning mechanism, the model of dual-reasoning-kernel can significantly improve inference accuracy and the utilization rate of knowledge, whose comprehensive accurate rate reached 90%. The system filled the gap of contrast and achieved satisfactory results.