Literature DB >> 18276479

On fuzzy modeling using fuzzy neural networks with the back-propagation algorithm.

S I Horikawa1, T Furuhashi, Y Uchikawa.   

Abstract

A fuzzy modeling method using fuzzy neural networks with the backpropagation algorithm is presented. The method can identify the fuzzy model of a nonlinear system automatically. The feasibility of the method is examined using simple numerical data.

Year:  1992        PMID： 18276479     DOI： 10.1109/72.159069

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw        ISSN： 1045-9227


  7 in total

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2.  Survey on Neural Networks Used for Medical Image Processing.

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3.  Cancer diagnosis marker extraction for soft tissue sarcomas based on gene expression profiling data by using projective adaptive resonance theory (PART) filtering method.

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4.  Artificial Neural Networks-Based Software for Measuring Heat Collection Rate and Heat Loss Coefficient of Water-in-Glass Evacuated Tube Solar Water Heaters.

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6.  Combinational risk factors of metabolic syndrome identified by fuzzy neural network analysis of health-check data.

Authors:  Yasunori Ushida; Ryuji Kato; Kosuke Niwa; Daisuke Tanimura; Hideo Izawa; Kenji Yasui; Tomokazu Takase; Yasuko Yoshida; Mitsuo Kawase; Tsutomu Yoshida; Toyoaki Murohara; Hiroyuki Honda
Journal:  BMC Med Inform Decis Mak       Date:  2012-08-01       Impact factor: 2.796

7.  An improved advertising CTR prediction approach based on the fuzzy deep neural network.

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Journal:  PLoS One       Date:  2018-05-04       Impact factor: 3.240
  7 in total

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