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2021 Vol.54, Issue 12S Preview Page

Research Article

31 December 2021. pp. 1119-1130
Abstract
References
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Lee, S.M., Kim, J.C., Jung, H.S., Lee, M.J., and Lee, S.R. (2017). "Prediction of flood susceptibility using random-forest and boosted-tree models in Seoul Metropolitan City, Korea." Geomatics, Natural Hazards and Risk, Vol. 3, No. 2, pp. 1185-1203. 10.1080/19475705.2017.1308971
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Mosavi, A., Ozturk, P., and Chaw, K.K. (2018). "Flood prediction using machine learning models: Literature review." Water, Vol. 10. doi: 10.3390/w10111536 10.3390/w10111536
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Park, J.H., Kim, S.H., and Bae, D.H. (2019). "Evaluating appropriateness of the design methodology for urban sewer system." Journal of Korea Water Resource Association, Vol. 52, No. 6, pp.411-420. (in Korean)
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Risi, R.D., Jalayer, F., and Paola, F.D. (2015). "Meso-scale hazard zoning of potentially flood prone areas." Journal of Hydrology, Vol. 527, pp. 316-325. 10.1016/j.jhydrol.2015.04.070
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Zhou, J.Z., Peng, T., Zhang, C., and Sun, N. (2018). "Data pre-analysis and ensemble of varios artificial neural networks for monthly streamflow forecasting." Water, Vol. 10, No. 5. doi: 10.3390/w10050628 10.3390/w10050628
Information
  • Publisher :KOREA WATER RESOURECES ASSOCIATION
  • Publisher(Ko) :한국수자원학회
  • Journal Title :Journal of Korea Water Resources Association
  • Journal Title(Ko) :한국수자원학회 논문집
  • Volume : 54
  • No :12
  • Pages :1119-1130
  • Received Date :2021. 09. 30
  • Revised Date :2021. 11. 01
  • Accepted Date : 2021. 11. 03