Applicability of Generalized Neural Network-Type SIRMs Method in Medical Data(<Special Issue>COMPUTATIONAL INTELLIGENCE)

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概要

• 論文の詳細を見る

• The single input rule modules connected fuzzy inference method (SIRMs method) is pre-sented by Yubazaki et al. which provide same number of fuzzy rules modules as input variables. Af-terward, Seki et al. has proposed the functional-type SIRMs method (F-SIRMs method) by replacing a constant term of the consequent part of the SIRMs method with a function. This study aims to find the way to improve effectiveness of the F-SIRMs method and apply to use in medical area. The techniques in this study include multi-layer perceptrons with back propagation learning method (MLP with BP), F-SIRMs method, the generalized neural network type SIRMs method (G-NN-SIRMs method). All techniques are produced to diagnosis of the liver ailment and diabetes. The data are divided into 2 parts i.e., for training and testing and run 10 simulations. Their results are compared in order to give the lower mean square error and higher accuracy. Judging from the results of experiment, the new proposed technique gives the higher performance than conventional methods.

• バイオメディカル・ファジィ・システム学会の論文

著者

• ISHII Hiroaki

  Dept. of Applied Physics, Faculty of Eng., Osaka University

• ISHII Hiroaki

  Dept. of Mathematical Sciences, Kwansei Gakuin University

• KUMDEE Orrawan

  Technology of Information System ,Management, Faculty of Engineering, Mahidol University

• SEKI Hirosato

  Dept. of Technology Management, Osaka Institute of Technology

関連論文

• A NEW ALGORITHM : FOR LOWER BOUNDS OF ALL-TERMINAL RELIABILITY
• Applicability of Generalized Neural Network-Type SIRMs Method in Medical Data(COMPUTATIONAL INTELLIGENCE)

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