Evolving fuzzy rule-based models

Angelov, Plamen (1999) Evolving fuzzy rule-based models. In: 8th IFSA World Congress, 1999-08-171999-08-20.

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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.

Item Type: Contribution to Conference (Paper)
Journal or Publication Title: 8th IFSA World Congress
Uncontrolled Keywords: /dk/atira/pure/researchoutput/libraryofcongress/qa75
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 957
Deposited By: Dr. Plamen Angelov
Deposited On: 11 Jan 2008 11:14
Refereed?: Yes
Published?: Published
Last Modified: 25 Jan 2020 06:02
URI: https://eprints.lancs.ac.uk/id/eprint/957

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