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

Krzysztof Simiński

International Journal of Applied Mathematics and Computer Science (2010)

  • Volume: 20, Issue: 2, page 337-347
  • ISSN: 1641-876X

Abstract

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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.

How to cite

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Krzysztof Simiński. "Rule weights in a neuro-fuzzy system with a hierarchical domain partition." International Journal of Applied Mathematics and Computer Science 20.2 (2010): 337-347. <http://eudml.org/doc/207991>.

@article{KrzysztofSimiński2010,
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.},
author = {Krzysztof Simiński},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {fuzzy inference system; hierarchical input domain partition; rule weights},
language = {eng},
number = {2},
pages = {337-347},
title = {Rule weights in a neuro-fuzzy system with a hierarchical domain partition},
url = {http://eudml.org/doc/207991},
volume = {20},
year = {2010},
}

TY - JOUR
AU - Krzysztof Simiński
TI - Rule weights in a neuro-fuzzy system with a hierarchical domain partition
JO - International Journal of Applied Mathematics and Computer Science
PY - 2010
VL - 20
IS - 2
SP - 337
EP - 347
AB - 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.
LA - eng
KW - fuzzy inference system; hierarchical input domain partition; rule weights
UR - http://eudml.org/doc/207991
ER -

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