KIEE International Transaction on Electrical Machinery and Energy Conversion Systems

대한전기학회 (The Korean Institute of Electrical Engineers)
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Optimum Design of a Linear Induction Motor Using Genetic Algorithm, Niching GA and Neural Network

  • 발행 : 2003.09.01
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초록

This paper presents the optimum design of a Linear Induction Motor (LIM) using Genetic algorithm, Niching Genetic algorithm and Neural Network. The design variables are optimized by different optimization methods and the results are discussed.

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참고문헌

  1. K.Fujisaki, J.Nakagawa, H.Misumi, 'Fundamental characteristics of molten metal flow control by linear induction motor,' IEEE Trans. on Magnetics, vol. 30, no. 6,pp. 4764-4766, 1994
  2. David E. Goldberg, Genetic Algorithm in Search, Optimization, and Machine Learning, Addison Wesley, 1989
  3. B. Sareni, L. Krahenbuhl and A. Nicolas, 'Niching Genetic Algorithms for Optimization in Electromag-netics,' The $11^{th}$ COMPUMAG'97, pp. 563-564, Rio de Janeiro, 1997
  4. D.A. Lowther, W. Mai, 'A Comparison of MRI Mag-net Design using a Hopfield Network and the Opti-mized Material Distribution Method,' IEEE Trans. on Magnetics, vol. 34, no. 5, pp. 2885-2888, 1998
  5. Dal-Ho Im, Cheol-Jick Ree, Seung-Chan Park, 'Opti-mization of Design Variables of SLIM Using the Equivalent Circuit Analysis and SUMT,' KIEE Trans., vol. 42, no. 5, pp. 340-343, 1993