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  • 标题:A New ANFIS Model based on Multi-Input Hamacher T-norm and Subtract Clustering
  • 本地全文:下载
  • 作者:Feng-Yi Zhang ; Zhi-Gao Liao
  • 期刊名称:The Open Cybernetics & Systemics Journal
  • 电子版ISSN:1874-110X
  • 出版年度:2014
  • 卷号:8
  • 期号:1
  • 页码:829-834
  • DOI:10.2174/1874110X01408010829
  • 出版社:Bentham Science Publishers Ltd
  • 摘要:

    This paper proposed a novel adaptive neuro-fuzzy inference system (ANFIS), which combines subtract clustering, employs adaptive Hamacher T-norm and improves the prediction ability of ANFIS. The expression of multi-input Hamacher T-norm and its relative feather has been originally given, which supports the operation of the proposed system. Empirical study has testified that the proposed model overweighs early work in the aspect of benchmark Box-Jenkins dataset and may provide a practical way to measure the importance of each rule.

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