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    block this user An-Ping Li

    Research Fellow

    Beijing 100085, P.R.China

    A Knowledge-Based Neurocomputing Approach to Extract Refined Linguistic Rules from Data

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    This paper proposes a knowledge-based neurocomputing approach to extract and refine a set of linguistic rules from data. A neural network is designed along with its learning algorithm that allows simultaneous definition of the structure and the parameters of the rule base. The network can be regarded both as an adaptive rule-based system with the capability of learning fuzzy rules from data, and as a connectionist architecture provided with linguistic meaning. Experimental results on two well-known classification problems illustrate the effectiveness of the proposed approach.

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    Description

    Title : A Knowledge-Based Neurocomputing Approach to Extract Refined Linguistic Rules from Data
    Abstract : This paper proposes a knowledge-based neurocomputing approach to extract and refine a set of linguistic rules from data. A neural network is designed along with its learning algorithm that allows simultaneous definition of the structure and the parameters of the rule base. The network can be regarded both as an adaptive rule-based system with the capability of learning fuzzy rules from data, and as a connectionist architecture provided with linguistic meaning. Experimental results on two well-known classification problems illustrate the effectiveness of the proposed approach.
    Subject : unspecified
    Area : Mathematics
    Language : English
    Affiliations
    Url : http://www.di.uniba.it/~castella/papers/AIxIA2001.pdf
    Doi : 10.1.1.17.4772

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    An-Ping's Peer Evaluation activity

    Emailed by 1
    • Anonymous : 1
    Downloads 760
    Views 531
    Full text requests 9
    Followed by 2

    An-Ping has...

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