Nonlinear Function Approximation Based on Fuzzy Algorithms with Parameterized Conjunctors

In this study, two fuzzy algorithms, type-1 fuzzy algorithm with parameterized conjunctors and a novel approach interval type-2 fuzzy algorithm with parameterized conjunctors are used in the modeling application for nonlinear functions. The aim of using parameterized conjunctors as fuzzy operators in these algorithms is not to lose or distort the expert knowledge about the system during the optimization process. In this study, this linguistic information about the system is obtained by using fuzzy c-means clustering algorithms. Then, the designed fuzzy algorithms are tested on two benchmark nonlinear functions in modeling application.