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Information Journal Paper

Title

INTEGRATED ADAPTIVE FUZZY CLUSTERING (IAFC) NEURAL NETWORKS USING FUZZY LEARNING RULES

Pages

  1-13

Abstract

 The proposed IAFC neural networks have both the stability and the plasticity because they use the control structure which is similar to that of the ART-1(Adaptive Resonance Theory) neural network. The unsupervised IAFC neural network is the unsupervised neural network which uses the fuzzy leaky learning rule. This fuzzy leaky learning rule controls the updating amounts by membership values. The supervised IAFC neural networks are the supervised neural networks which use the fuzzified versions of Learning Vector Quantization (LVQ). In this paper, several important adaptive learning algorithms are also compared in the viewpoint of structure and learning rule. The performances of several adaptive learning algorithms are compared using Iris data.

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    • Cite

    APA: Copy

    KIM, Y.S., & ZENN BIEN, Z.. (2005). INTEGRATED ADAPTIVE FUZZY CLUSTERING (IAFC) NEURAL NETWORKS USING FUZZY LEARNING RULES. IRANIAN JOURNAL OF FUZZY SYSTEMS, 2(2), 1-13. SID. https://sid.ir/paper/113414/en

    Vancouver: Copy

    KIM Y.S., ZENN BIEN Z.. INTEGRATED ADAPTIVE FUZZY CLUSTERING (IAFC) NEURAL NETWORKS USING FUZZY LEARNING RULES. IRANIAN JOURNAL OF FUZZY SYSTEMS[Internet]. 2005;2(2):1-13. Available from: https://sid.ir/paper/113414/en

    IEEE: Copy

    Y.S. KIM, and Z. ZENN BIEN, “INTEGRATED ADAPTIVE FUZZY CLUSTERING (IAFC) NEURAL NETWORKS USING FUZZY LEARNING RULES,” IRANIAN JOURNAL OF FUZZY SYSTEMS, vol. 2, no. 2, pp. 1–13, 2005, [Online]. Available: https://sid.ir/paper/113414/en

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