Intelligent-Aided Design for Control Parameters of Kitchen Waste Pretreatment Based on the Specific Bayesian Network Expert System

Kitchen waste treatment is an essential issue in the process of urbanization. Aiming at problems such as the dependence of engineer experience on the parameter setting of various equipment in the whole process of kitchen waste pretreatment, the failure to adapt to the characteristics of kitchen waste, and poor overall performance, this paper studies the intelligent assistant design method of kitchen waste pretreatment control parameters based on Bayesian network expert system. The overall framework of the kitchen waste pretreatment process was built using the experience of experts in the kitchen waste industry, and the correlation network between kitchen waste characteristics and pretreatment equipment parameters was established to form a Bayesian causal probability table. The Bayesian network structure was built to realize the inference prediction of equipment parameter changes based on the characteristics of kitchen waste. The verification experiment shows that the design performs well in the kitchen waste pretreatment parameter decision. It provides a feasible scheme for effectively solving the problem of kitchen waste pretreatment.