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Integration of Taguchi's method and multiple-input, multiple-output ANFIS inverse model for the optimal design of a water-cooled condenser.

Author(s) : HUANG C. N., YU C. C.

Type of article: Article

Summary

The design of water-cooled condensers is a typical nonlinear and multiple-input, multiple-output (MIMO) problem; to achieve optimal performance, Taguchi's method and inverse-model technology were integrated, and a simulation platform developed by using the COMSOL Multiphysics software was used. First, the minimum number of experiments required to represent the full-factorial design and the most critical factors affecting product performance were determined by using Taguchi's method. Next, the adaptive neuro-fuzzy inference system (ANFIS) was extended to an MIMO–ANFIS architecture and used to train an inverse model for realizing the desired design. By using a well-trained model that can determine the inverse relationship of each input–output set, the manufacturing parameters for the optimal performance were obtained. A simulation study on a water-cooled condenser is presented to demonstrate the effectiveness of the proposed method.

Details

  • Original title: Integration of Taguchi's method and multiple-input, multiple-output ANFIS inverse model for the optimal design of a water-cooled condenser.
  • Record ID : 30017615
  • Languages: English
  • Source: Applied Thermal Engineering - vol. 98
  • Publication date: 2016/04/05
  • DOI: http://dx.doi.org/10.1016/j.applthermaleng.2015.11.112

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