Journal of the Korean Operations Research and Management Science Society (한국경영과학회지)

The Korean Operations Research and Management Science Society (한국경영과학회)
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Structure Design of Artificial Neural Networks using Genetic Algorithm

유전적 알고리즘을 이용한 인공신경망의 구조 설계

  • 이재식 (아주대학교 경영대학 경영학부) ;
  • 차봉근 (IBM Korea 보험산업서비스 사업부)
  • Published : 1999.09.01
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Abstract

Artificial Neural Networks(ANN) have been successfully applied to various kinds of business and engineering problems, especially those involved in pattern classification. However, because of the lack of design standard or guidelines, the structure of specific ANN depends on the designer's own experiments or choices. In other words, even though we could construct a better ANN, we often steeled down with just a satisfactory ANN. The purpose of this research is to apply the Genetic Algorithm(GA) to design a structure of ANN that yields better performance compared to the existing test results. For a bankruptcy prediction problem. an exiting research using ANN which consists of 22 input processing elements(PEs) for financial ratios and 5 hidden PEs showed 70% hit ratio. In our research, the input financial ratios and the number of hidden PEs are determined by GA. The best ANN, which consists of 8 input PEs and 6 hidden PEs, shows 78.03% hit ratio. In addition, we compare the performance of two types of reproduction schemes, i.e., generational reproduction and steady-state reproduction.

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References

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