A Fuzzy Lagrange_s Interpolative Reasoning Method Based on Geometric Parameter

When rule bases are sparse, we cannot get any reasoning result by traditional fuzzy reasoning method because an observation is in the gap between two neighboring antecedents. But authors have proved that fuzzy reasoning is really equal to interpolation. Hence Koczy and Hirota first proposed KH linear interpolative reasoning method. But its consequence does not always keep convexity and normality under many conditions. In order to get better result, this paper presents a fuzzy Lagrange´s interpolative method based geometric parameter. Reasoning is simple by the method; moreover it can keep the convexity of the reasoning consequence.