Evolving fuzzy linear regression trees

Author

Lemos, Andre ; Caminhas, Walmir ; Gomide, Fernando

Author_Institution

Dept. of Electr. Eng., Fed. Univ. of Minas Gerais, Belo Horizonte, Brazil

fYear

2010

fDate

18-23 July 2010

Firstpage

1

Lastpage

8

Abstract

This paper introduces a new approach for evolving fuzzy modeling based on a tree structure. The system is a fuzzy linear regression tree whose topology can be continuously updated using a statistical model selection test. A fuzzy linear regression tree is a fuzzy tree with linear model in each leaf. The evolving linear regression approach is evaluated on a forecasting problem and its performance compared against alternative evolving fuzzy models and classic models with fixed structures. The results suggest that evolving fuzzy regression tree is a promising approach for adaptive system modeling.

Keywords

forecasting theory; fuzzy set theory; regression analysis; statistical testing; topology; trees (mathematics); adaptive system modeling; evolving fuzzy modeling; evolving fuzzy regression tree; forecasting problem; fuzzy linear regression trees; linear model; statistical model selection test; topology; tree structure; Adaptation model; Computational modeling; Data models; Fuzzy sets; Input variables; Linear regression; Regression tree analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems (FUZZ), 2010 IEEE International Conference on

Conference_Location

Barcelona

ISSN

1098-7584

Print_ISBN

978-1-4244-6919-2

Type

conf

DOI

10.1109/FUZZY.2010.5583970

Filename

5583970