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    GA-based learning algorithms to identify fuzzy rules for fuzzy neural networks

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    Publication date
    2007
    Author
    Aimejalii, K.
    Dahal, Keshav P.
    Hossain, M. Alamgir
    Keyword
    Fuzzy neural networks
    Fuzzy rules
    Genetic algorithms
    Rights
    Copyright © [2007] IEEE. Reprinted from Seventh International Conference on Intelligent Systems Design and Applications, ISDA 2007. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bradford's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubspermissions@ ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it
    Peer-Reviewed
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    Abstract
    Identification of fuzzy rules is an important issue in designing of a fuzzy neural network (FNN). However, there is no systematic design procedure at present. In this paper we present a genetic algorithm (GA) based learning algorithm to make use of the known membership function to identify the fuzzy rules form a large set of all possible rules. The proposed learning algorithm initially considers all possible rules then uses the training data and the fitness function to perform ruleselection. The proposed GA based learning algorithm has been tested with two different sets of training data. The results obtained from the experiments are promising and demonstrate that the proposed GA based learning algorithm can provide a reliable mechanism for fuzzy rule selection.
    URI
    http://hdl.handle.net/10454/2553
    Version
    Accepted Manuscript
    Citation
    Aimejalii, K., Dahal, K. and Hossain, A. (2007) GA-based learning algorithms to identify fuzzy rules for fuzzy neural networks. In: Seventh International Conference on Intelligent Systems Design and Applications, ISDA 2007, Rio de Janeiro, 20-24th Oct., 2007. New York: IEEE.
    Link to publisher’s version
    http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=4389623
    Type
    Conference paper
    Collections
    Engineering and Informatics Publications

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