최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기韓國地盤工學會論文集 = Journal of the Korean geotechnical society, v.37 no.12, 2021년, pp.117 - 125
김준영 (한남대학교 스마트융합공학부) , 강재모 (한국건설기술연구원 지반연구본부) , 백성하 (한국건설기술연구원 지반연구본부)
The occurrence of ground subsidence and sinkhole in downtown areas, which threatens the safety of citizens, has been frequently reported. Among the various mechanisms of a sinkhole, soil erosion through the damaged part of the sewer pipe was found to be the main cause in Seoul. In this study, a rand...
Bae, Y., Shin, S.,Won, J., and Lee, D. (2016), "The Road Subsidence Conditions and Safety Improvement Plans in Seoul", 2016-PR-09, The Seoul Institute.
Chen, W., Xie, X., Wang, J., Pradhan, B., Hong, H., Bui, D. T.,... and Ma, J. (2017), A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility, Catena, Vol.151, pp. 147-160.
Guo, S., Shao, Y., Zhang, T., Zhu, D.Z., Asce, M., and Zhang, Y. (2013), "Physical Modeling on Sand Erosion around Defective Sewer Pipes under the Influence of Groundwater", Journal of Hydraulic Engineering, Vol.139, pp.1247-1257.
Hosmer, D. W., Lemeshow, S., and Rodney, X. S. (2000), Applied logistic regression, Wiley, New York.
Indiketiya, S., Jegatheesan, P., and Pathmanathan, R. (2017), "Evaluation of Defective Sewer Pipe Induced Internal Erosion and Associated Ground Deformation Using Laboratory Model Test", Canadian Geotechnical Journal, Vol.54, pp.1184-1195.
Korea Institute of Civil Engineering and Building Technology (2020), "Underground Space DB Accuracy Improvement and Underground Utilities Safe Management Technology", KICT 2020-215.
Korea Institute of Geoscience and Mineral Resources (2014), "A Study on the Causes and Policy Recommendations of Sinkholes", Final Report.
Kim, C ., Jung, J., C hoi, C ., and Yoo, W. (2015), "Causes of Ground Subsidence (Sinkholes), Technology and Policy Countermeasures", Ssangyong Engineering & Construction Research Institute, Vol.71, pp.17-25.
Kim, K., Kim, J., Kwak, T. Y., and Chung, C. K. (2018), Logistic regression model for sinkhole susceptibility due to damaged sewer pipes, Natural Hazards, Vol.93, No.2, pp.765-785.
Kuwano, R., Horii, T., Yamauchi, K., and Kohashi, H. (2010), "Formation of Subsurface Cavity and Loosening due to Defected Sewer Pipes", Japanese Geotechnical Journal, Vol.5, pp.349-361.
Kwak, T. Y., Woo, S. I., Kim, J., and Chung, C. K. (2019), "Model Test Assessment of the Generation of Underground Cavities and Ground Cave-ins by Damaged Sewer Pipes", Soils and Foundations, Vol.59, pp.586-600.
Kwak, T. Y., Woo, S. I., Chung, C. K., and Kim, J. (2020), "Experimental Assessment of the Relationship between Rainfall Intensity and Sinkholes Caused by Damaged Sewer Pipes", Natural Hazards and Earth System Sciences, Vol.20, pp.3343-3359.
Matin, S. S., Farahzadi, L., Makaremi, S., C helgani, S. C ., and Sattari, G. (2018), "Variable Selection and Prediction of Uniaxial Compressive Strength and Modulus of Elasticity by Random Forest", Applied Soft Computing, Vol.70, pp.980-987.
Mukunoki, T., Kumano, N., Otani, J., and Kuwano, R. (2009), "Visualization of Three Dimensional Failure in Sand due to Water Inflow and Soil Drainage from Defective Underground Pipe Using X-Ray CT", Soils and Foundations, Vol.49, pp.959-968.
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., ... and Duchesnay, E. (2011), "Scikit-learn: Machine Learning in Python. the Journal of machine Learning research", Vol.12, pp.2825-2830.
Sato, M. and Kuwano, R. (2015), "Influence of Location of Subsurface Structures on Development of Underground Cavities Induced by Internal Erosion", Soils and Foundations, Vol.55, pp.829-840.
Sun, D., Xu, J., Wen, H., and Wang, D. (2021), "Assessment of Landslide Susceptibility Mapping based on Bayesian Hyperparameter Optimization: A Comparison between Logistic Regression and Random Forest", Engineering Geology, Vol.281, 105972.
Yokota, T., Fukatani, W., and Miyamoto, T. (2012), "The Present Situation of the Road Cave in Sinkholes Caused by Sewer Systems".
Zhang, W., Wu, C., Zhong, H., Li, Y., and Wang, L. (2021), "Prediction of Undrained Shear Strength Using Extreme Gradient Boosting and Random Forest based on Bayesian Optimization", Geoscience Frontiers, Vol.12, No.1, pp.469-477.
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
오픈액세스 학술지에 출판된 논문
※ AI-Helper는 부적절한 답변을 할 수 있습니다.