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Evolving fuzzy rule-based models

Research output: Contribution to conference - Without ISBN/ISSN Conference paperpeer-review

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Evolving fuzzy rule-based models. / Angelov, Plamen.
1999. 19-23 Paper presented at 8th IFSA World Congress, Taipei, Taiwan.

Research output: Contribution to conference - Without ISBN/ISSN Conference paperpeer-review

Harvard

Angelov, P 1999, 'Evolving fuzzy rule-based models', Paper presented at 8th IFSA World Congress, Taipei, Taiwan, 17/08/99 - 20/08/99 pp. 19-23.

APA

Angelov, P. (1999). Evolving fuzzy rule-based models. 19-23. Paper presented at 8th IFSA World Congress, Taipei, Taiwan.

Vancouver

Angelov P. Evolving fuzzy rule-based models. 1999. Paper presented at 8th IFSA World Congress, Taipei, Taiwan.

Author

Angelov, Plamen. / Evolving fuzzy rule-based models. Paper presented at 8th IFSA World Congress, Taipei, Taiwan.5 p.

Bibtex

@conference{9a8f7b5957404c60a0f2916a03f0de11,
title = "Evolving fuzzy rule-based models",
abstract = "An approach to auto-generation of fuzzy rule-based models is proposed in the paper. Its main advantage is the high flexibility: no a priory information about the model structure is necessary. A new efficient coding procedure is proposed instead of usually used coding of all possible fuzzy rules into a chromosome. Parameter and structure identifications are realized by optimization at two stages. First, the best k rules are determined such that to minimize the root square error. At the second stage, GA tunes parameters of the membership functions and singletons. Software, which realizes the approach in the framework of Matlab v.5.2, is designed. Modeling of thermal load of a building is considered in order to illustrate the applicability of the approach.",
keywords = "DCS-publications-id, inproc-347, DCS-publications-personnel-id, 82",
author = "Plamen Angelov",
year = "1999",
month = aug,
day = "17",
language = "English",
pages = "19--23",
note = "8th IFSA World Congress ; Conference date: 17-08-1999 Through 20-08-1999",

}

RIS

TY - CONF

T1 - Evolving fuzzy rule-based models

AU - Angelov, Plamen

PY - 1999/8/17

Y1 - 1999/8/17

N2 - An approach to auto-generation of fuzzy rule-based models is proposed in the paper. Its main advantage is the high flexibility: no a priory information about the model structure is necessary. A new efficient coding procedure is proposed instead of usually used coding of all possible fuzzy rules into a chromosome. Parameter and structure identifications are realized by optimization at two stages. First, the best k rules are determined such that to minimize the root square error. At the second stage, GA tunes parameters of the membership functions and singletons. Software, which realizes the approach in the framework of Matlab v.5.2, is designed. Modeling of thermal load of a building is considered in order to illustrate the applicability of the approach.

AB - An approach to auto-generation of fuzzy rule-based models is proposed in the paper. Its main advantage is the high flexibility: no a priory information about the model structure is necessary. A new efficient coding procedure is proposed instead of usually used coding of all possible fuzzy rules into a chromosome. Parameter and structure identifications are realized by optimization at two stages. First, the best k rules are determined such that to minimize the root square error. At the second stage, GA tunes parameters of the membership functions and singletons. Software, which realizes the approach in the framework of Matlab v.5.2, is designed. Modeling of thermal load of a building is considered in order to illustrate the applicability of the approach.

KW - DCS-publications-id

KW - inproc-347

KW - DCS-publications-personnel-id

KW - 82

M3 - Conference paper

SP - 19

EP - 23

T2 - 8th IFSA World Congress

Y2 - 17 August 1999 through 20 August 1999

ER -