Linear and non-linear fuzzy regression: Evolutionary algorithm solutions

Given some data, which consists of pairs of fuzzy numbers, our evolutionary algorithm searches our library of fuzzy functions (which includes linear, polynomial, exponential and logarithmic) for a fuzzy function which best fits the data. Tests of our fuzzy regression package are given For each of the four cases: linear, polynomial, exponential and logarithmic. For the linear model we also consider multiple independent variables. In all cases we use data generated with and without noise. We prove that fuzzy polynomial regression can model the extension principle extension of continuous real-valued functions. (C) 2000 Elsevier Science B.V. All rights reserved.