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- W1520853569 abstract "This paper is concerned with the problem of constructing a fuzzy model from numerical data through a self-organizing counter propagation network (SOCPN). Two self-organizing algorithms, unsupervised USOCPN and supervised SSOCPN, are introduced. SOCPN can be employed in two ways. It can be used as a knowledge extractor by which a set of rules are generated from the available numerical data set. The generated rule-base is then utilized by a fuzzy reasoning model. It can also be used as an online adaptive fuzzy model in which the rule-base in terms of connection weights is updated successively in response to the incoming measured data. The simulation results on some well studied examples are given." @default.
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- W1520853569 date "2005-08-25" @default.
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- W1520853569 title "A neural approach to fuzzy modeling" @default.
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- W1520853569 doi "https://doi.org/10.1109/acc.1994.752454" @default.
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