Treffer: A methodology for constructing fuzzy rule based classification systems: A methodology for construction fuzzy rule-based classification systems

Title:
A methodology for constructing fuzzy rule based classification systems: A methodology for construction fuzzy rule-based classification systems
Authors:
Fernández Garrido, José María, Requena Ramos, Ignacio
Source:
UPCommons. Portal del coneixement obert de la UPC
Universitat Politècnica de Catalunya (UPC)
Mathware & soft computing; 2000: Vol.: 7 Núm.: 2-3
Publisher Information:
Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica, 2000.
Publication Year:
2000
Subject Terms:
Classificació AMS::90 Operations research, Computing methodologies and applications, Classification Systems, Systems Genetic Algorithms, fuzzy rules, mathematical programming::90C Mathematical programming, Classification Systems, Systems Genetic Algorithms, 90 Operations research, mathematical programming::90C Mathematical programming [Classificació AMS], Classificació AMS::90 Operations research, mathematical programming::90C Mathematical programming, Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence, fuzzy network, Systems based on Fuzzy Rules, Programació (Matemàtica), Sistemes experts (Informàtica)
Document Type:
Fachzeitschrift Article
File Description:
application/pdf; application/xml; text/html
Language:
English
Access URL:
https://hdl.handle.net/2099/3576
http://hdl.handle.net/2099/3576
https://zbmath.org/1648848
http://www.raco.cat/index.php/Mathware/article/view/84817
Rights:
CC BY NC ND
Accession Number:
edsair.dedup.wf.002..e0e2e40d88214e78214fdcc726c81851
Database:
OpenAIRE

Weitere Informationen

In this paper, a methodology to obtain a set of fuzzy rules for classification systems is presented. The system is represented in a layered fuzzy network, in which the links from input to hidden nodes represents the antecedents of the rules, and the consequents are represented by links from hidden to output nodes. Specific genetic algorithms are used in two phases to extract the rules. In the first phase an initial version of the rules is extracted, and in second one, the labels are refined. The procedure is illustrated by applying it to two real-world classification problems