Abstract:
An expert system with multiple objectives programming for aerator selection was established. The database of the system, containing various parameters of 172 types of aerators and some If Then rules, was made using MS Access. The inference mechanism in the system, involving forward chaining and backward chaining, contains a model of multiple objectives programming. Through applying the expert system, users may find aerators that achieve comprehensive optimization simultaneously with respect to those targets of the purchase fee, the operation fee, the area of aeration basin, as well as the treatment efficiency. An application showed that the expert system is effective.