Robustification of ANFIS Based on Noise Fuzzy Clustering Concept

Abstract

Adaptive Network-based Fuzzy Inference System (ANFIS) is a promising model of explainable neural networks but rejection of illegal noise effects is an important issue in real application. In this research, a novel approach for introducing the noise clustering concept into fuzzy c-means-based ANFIS is proposed for robust modeling, which simultaneously considers two types of noise generation schemes of input-level noise and output-level noise.