Fuzzy Intelligent Decision Tree Model and Its Application

Abstract

Decision making is one of the core problems of computational intelligence. Based on the theory of fuzzy mathematics, a general fuzzy decision tree model is established. The nodes are used to describe the decision premise and control information, and the edges of the tree are used to formalize the reasoning rules. The reasonable fuzzy decision operators are defined on the nodes and the edges to make a multi-level comprehensive decision. Engineering decisions consider the costs, feasibility, and benefits of different options. The fusion of these information is used to measure the merits and demerits of decision making schemes. The weighted fuzzy intelligent decision-making model is established, and the algorithm of multi-attribute constrained decision-making based on the model is given. The complexity of the model and algorithm is discussed. Finally, through two application examples, it is proven that the decision model and the algorithm of optimal decision scheme consider qualitative and quantitative information, and the decision result is scientific and reasonable with large amount of information.

Keywords

• |fuzzy decision tree|limited decision|optimal decision|weighting function