Journal of the Korean Geotechnical Society (한국지반공학회논문집)

Korean Geotechnical Society (한국지반공학회)
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Assessment of Landslide Causal Factors Using ANN Method

ANN 기법을 이용한 사면 붕괴인자 평가

  • Received : 2012.07.27
  • Accepted : 2012.10.18
  • Published : 2012.10.28
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Abstract

In this study landslide causal factors which are considered to have the same effect in assessment techniques are categorized and their impact on landslides is analyzed to acquire reasonable weighting factors in the landslide hazard. Results are compared to those of the Assessment Chart developed by National Institute for Disaster Prevention (NIDP) and the adequacy and proper portion for landslide causal factors are considered. The Artificial Neural Network (ANN) method applied to 28 landslide areas is incorporated to evaluate the reasonable rating. Results show that the following items in the Chart are necessary to modify their portions in order to implement the precise assessment results: 1) Estimated damage; 2) Tension crack; 3) Existence of valley.

본 연구에서는 사면위험도의 합리적인 평가 가중치를 도출하기 위하여 국내의 대표적인 평가방법에 대해 동일한 영향성을 주는 것으로 간주되는 항목들을 그룹화하여 그 영향성을 분석하고 이를 국립방재연구소(NIDP) 평가법과 비교, 사면붕괴 주요인자 선별의 적정성과 배점비율을 검토하였다. 또한, 붕괴가 발생된 28개소 사면을 대상으로 ANN(Artificial Neural Network) 기법을 적용하여 사면붕괴 유발인자 가중치에 대한 합리적 배점이 이루어졌는지에 대해 고찰하였다. ANN기법에 의해 평가비중을 재조정하여 분석한 결과, 국립방재연구소 평가법의 평가비중 오차가 큰 예상피해도, 인장균열, 계곡부 항목의 가중치를 조정하여야 보다 정확한 평가가 가능할 것으로 분석되었다.

Keywords

References

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