A soft-sensing method of dissolved oxygen concentration by group genetic case-based reasoning with integrating group decision making
To estimate the dissolved oxygen (DO) concentration in the wastewater treatment process more accurately, a group genetic case-based reasoning (GGCBR) soft-sensing method of DO concentration is proposed by the integrated use of genetic algorithms (GA) and group decision making (GDM) in this paper. First, an attribute weight iterative optimization using GA is discussed in the case retrieval phase. Then, a case reuse method is carried out by using the GDM theory. Finally, the historical data of DO concentration in a wastewater treatment process are used to carry out a comparison experiment by 10-fold cross validation. The results show that this proposed GGCBR is superior to other methods and significantly reduces the fitting error of DO concentration.
dissolved oxygen case-based reasoning genetic algorithms group decision-making