Parameterized interval valued fuzzy expert systems for feasibility study of projects

Fuzzy system models are enriched by interval valued sets. They can better represent the expert's knowledge and are more flexible and robust in decision-making. This paper addresses several parameterized models for combination of FDCF and FCCF, fuzzy conjunctive canonical form and fuzzy disjunctive canonical form. Then the optimal parameters are gained through an optimization method to assign the best membership functions for the variables of the system domain. The proposed expert system is implemented for feasibility study of the army projects. This system uses Schweizer and Sklar parametric operators for t-norm and s-norm and Yager parametric defuzzification method. Moreover, for inference mechanism, FATI and FITA are combined with a linear parameter. The presented expert system shows its superiority in comparison with type I fuzzy set in flexibility, and robustness.