Journal of Advanced Marine Engineering and Technology

The Korean Society of Marine Engineering (한국마린엔지니어링학회)
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Optimal Inner Case Design for Refrigerator by Utilizing Artificial Neural Networks and Genetic Algorithm

  • Zhai, Jianguang (Mechanical and Information Engineering, Korea Maritime University) ;
  • Cho, Jong-Rae (Mechanical and Information Engineering, Korea Maritime University) ;
  • Roh, Min-Shik (Underwater Vehicle Research Center)
  • Received : 2010.10.12
  • Accepted : 2010.11.30
  • Published : 2010.11.30
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Abstract

In this paper, an artificial neural network (ANN) was employed to build a predicting model for refrigerator structure. The predicting model includes three input variables of the plaque depth (D), width (W) and interval distance(S) on the inner wall. Finite element method was utilized to obtain the data, which would be necessary for the ANN training process. Finally, a genetic algorithm (GA) was applied to find the optimal parameters that leaded to the minimum inner case deformation under operating condition. The optimal combination found is the depth(D) of 2.63mm, the width(W) of 19.24mm and the interval distance(S) of 49.38mm which leaded to the smallest deformation of 1.88mm for the given refrigerator model.

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References

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