Piecewise Multilinear System Modeling Algorithms Using Numerical Data

Abstract

In this study, we proposed a piecewise modeling method using numerical data. The vertex values of hyperrectangular regions were determined using the learning algorithm based on a simplified fuzzy inference model because the piecewise model was represented by a fuzzy if-then rule with singleton consequents. The proposed algorithm can be used to determine the vertex values and positions of segmented regions and with minimum modeling errors. A example was considered to demonstrate the effectiveness of the proposed method using numerical simulations.