<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>The paper discusses the problem of rule weight tuning in neuro-fuzzy systems with parameterized consequences in which rule weights and the activation of the rules are not interchangeable. Some heuristic methods of rule weight computation in neuro-fuzzy systems with a hierarchical input domain partition and parameterized consequences are proposed. Several heuristics with experimental results showing the advantage of their usage are presented.</p></abstract>

The paper discusses the problem of rule weight tuning in neuro-fuzzy systems with parameterized consequences in which rule weights and the activation of the rules are not interchangeable. Some heuristic methods of rule weight computation in neuro-fuzzy systems with a hierarchical input domain partition and parameterized consequences are proposed. Several heuristics with experimental results showing the advantage of their usage are presented.

Rule weights in a neuro-fuzzy system with a hierarchical domain partition

Institute of Informatics, Silesian University of Technology, ul. Akademicka 16, 44-100 Gliwice, Poland

International Journal of Applied Mathematics and Computer Science

{"article-title":"Rule weights in a neuro-fuzzy system with a hierarchical domain partition"}

The paper discusses the problem of rule weight tuning in neuro-fuzzy systems with parameterized consequences in which rule weights and the activation of the...

Rule weights in a neuro-fuzzy system with a hierarchical domain partition

Publié en ligne: 02 juil. 2010

Pages: 337 - 347

DOI: https://doi.org/10.2478/v10006-010-0025-3

Mots clés
fuzzy inference system, hierarchical input domain partition, rule weights

This content is open access.

Rule weights in a neuro-fuzzy system with a hierarchical domain partition

Publié en ligne: 02 juil. 2010

Pages: 337 - 347

DOI: https://doi.org/10.2478/v10006-010-0025-3

Mots clésfuzzy inference system, hierarchical input domain partition, rule weights

This content is open access.

Mots clés
fuzzy inference system, hierarchical input domain partition, rule weights