Authors: Krause, P.
Krone, A.
Lindenblatt, M.
Slawinski, T.
Title: A Hybrid Evolutionary Search Concept for Data-based Generation of Relevant Fuzzy Rules in High Dimensional Spaces
Language (ISO): en
Abstract: In this paper we propose a hybrid fuzzy-evolutionary system for fuzzy modelling in high dimensional spaces. The system architecture is based on a Michigan-style approach (one individual represents one fuzzy rule). The design of the evolutionary algorithm makes use of a distance measure in the search space that in turn reflects some heuristic assumptions about the fitness landscape. Additionally, strategy parameters are dynamically adapted by means of a fuzzy controller. The approach is successfully applied to a complex benchmark problem as well as to several real-world modelling tasks such as the cancellation behaviour of insurance clients and the classification of automatic gearboxes.
Issue Date: 2001-10-16
Provenance: Universität Dortmund
Appears in Collections:Sonderforschungsbereich (SFB) 531

Files in This Item:
File Description SizeFormat 
ci50.pdfDNB670.62 kBAdobe PDFView/Open
ci50.ps2.01 MBPostscriptView/Open

This item is protected by original copyright

Items in Eldorado are protected by copyright, with all rights reserved, unless otherwise indicated.