A Weighted Adaptive Fuzzy Interpolation Method of Interval Type-2 Polygonal Fuzzy Sets

Adaptive fuzzy interpolative reasoning (AFIR) can overcome the limitation of the conventional fuzzy interpolation techniques because it can find and solve the contradictions of the fuzzy interpolative reasoning (FIR) results in order to ensure that the derived FIR results are consistent. The main contribution of this paper is that this paper proposes a weighted adaptive fuzzy interpolation method of interval type-2 polygonal fuzzy sets for sparse rule-based system. The proposed method includes a new contradiction solving method to get a high similarity degree between interval type-2 polygonal fuzzy sets of the fuzzy interpolative reasoning results. The experimental result shows that the proposed method can overcome the drawback of the existing method.