Constructing fuzzy models with linguistic integrity from numerical data-AFRELI algorithm

This paper presents an algorithm to extract rules re- lating input/output data and including prior knowledge. The rules are created in the environment of fuzzy systems. The fuzzy sets describing the system are constructed within a framework of lin- guistic integrity to guarantee its interpretability in the linguistic context. Two algorithms are presented in this paper. The main al- gorithm is the autonomous fuzzy rule extractor with linguistic in- tegrity (AFRELI). This algorithm is complemented with the use of the FuZion algorithm created to merge consecutive member- ship functions, while guaranteeing the distinguish ability between fuzzy sets. Comparisons with other proposed methods show a good tradeoff between accuracy and interpretability.