Journal of The Korean Society of Agricultural Engineers (한국농공학회논문집)

The Korean Society of Agricultural Engineers (한국농공학회)
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The Prediction of Compressive Strength of Sedimentary Rock using the Artificial Neural Networks

인공신경망을 이용한 퇴적암의 압축강도 예측

  • 이상호 (경북대학교 농업생명과학대학 농업토목공학과) ;
  • 김동락 (경산1대학교 철도토목과) ;
  • 서인식 (경산1대학교 철도토목과)
  • Received : 2012.05.07
  • Accepted : 2012.08.20
  • Published : 2012.09.30
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Abstract

A evaluation for the strength of rock includes a lot of uncertainty due to existence of discontinuity surface and weakness plain in the rock mass, so essential test results and other data for the resonable strength analysis are absolutely insufficient. Therefore, a analytical technique to reduce such uncertainty can be required. A probabilistic analysis technique has mainly to make up for the uncertainty to investigate the strength of rock mass. Recently, a artificial neural networks, as a more newly analysis method to solve several problems in the existing analysis methodology, trends to apply to study on the rock strength. In this study the unconfined compressive strength from basic physical property values of sedimentary rock, black shale and red shale, distributed in Daegu metropolitan area is estimated, using the artificial neural networks. And the applicability of the analysis method is investigated. From the results, it is confirmed that the unconfined compressive strength of the sedimentary rock can be easily and efficiently predicted by the analysis technique with the artificial neural networks.

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References

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