T-S fuzzy affine linear modeling algorithm by possibilistic c-regression models clustering algorithm
Chung‐Chun Kung, Hong-Chi Ku · 2014
This paper presents a Takagi-Sugeno (T-S) fuzzy affine linear modeling algorithm by the possibilistic c-regression models (PCRM) clustering algorithm. We apply the PCRM to partition the given input-output data into hyper-plane-shaped clusters (regression models). We choose the suitable number of cluster by the cluster validity criterion and then to construct the T-S fuzzy affine linear model. A simulation example is provided to demonstrate the effectiveness of the T-S fuzzy affine linear modeling algorithm.