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Journal of the Korean Society of Civil Engineers

Journal of the Korean Society of Civil Engineers

ISO Journal TitleKSCE J. Civ. Environ. Eng. Res.
  • Open Access, Bi-monthly

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  3. 2018-12 (v.38 n.6)
  4. 10.12652/Ksce.2018.38.6.0839
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1 
Bae, D. H., Shim, J. B. and Yoon, S. S. (2012). "Development and assesment of flow nomograph for the real-time flood forecasting in Cheonggye stream." Journal Korea Water Resour. Assoc., Vol. 45, No. 11, pp. 1107-1119 (in Korean).DOI
2 
Chang, F. J., Chang, L. C. and Wang, Y. S. (2007). "Enforced self-organizing map neural networks for river flood forecasting." Hydrological Process, Vol. 21, pp. 741-749.DOI
3 
Choi, H. G., Han, K. Y., Roh, H. S. and Park, S. J. (2013). "Comparison of data-based real-time flood forecasting model." Journal Korean Society of Civil Engineers, Vol. 33, No. 5, pp. 1809-1827 (in Korean).DOI
4 
Choi, S. M., Yoon, S. S. and Choi, Y. J. (2015). "Evaluation of high-resolution QPE data for urban runoff analysis." Journal Korea Water Resour. Assoc., Vol. 48, pp. 719-728 (in Korean).DOI
5 
Han, K. Y. (2012). Flood Disaster Mitigation. R&D Press.
6 
Huber, W. C. and Dickson, R. E. (1988). Storm Water Management Model. User's Manual Ver. 4, U.S. EPA.
7 
Jang, S. H., Yoon, J. Y. and Yoon, Y. N. (2006). "A study on the improvement of Huff's method in Korea: I. Review of applicability of Huff's method in Korea." Journal Korea Water Resour. Assoc, Vol. 39, pp. 767-777, doi:10.3741/JKWRA.2006.39.9.767 (in Korean with Englishabstract).DOI
8 
Jo, D. J. and Jeon, B. H. (2014). "Development of flood nomograph for inundation forecasting in urban districts." Journal of KOSHAM, Vol. 13, No. 3, pp. 37-42 (in Korean).
9 
Kalteh, A. M., Hjorth, P. and Berndtsson, R. (2008). "Review of the self-organizing map (SOM) approach in water resources : Analysis, modeling and application." Elsevier Environmental Modelling & software, Vol. 23, pp. 835-845.DOI
10 
Keum, H. J., Kim, H. I. and Han, K. Y. (2018). "Real-TIME forecast of rainfall impact on urban inundation." Journal of the Korean Association of Geographic Information Studies, Vol. 21, No. 3, pp. 76-91.
11 
Kim, H. I., Keum, H. J. and Han, K. Y. (2018). "Application and comparison of dynamic artificial neural networks for urban inundation analysis." Journal of the Korea Society of Civil Engineers, Vol. 38, No. 5, pp. 671-684 (in Korean).
12 
Lee, B. H. (2006). "A study on the characteristics and composition direction of urban flood control system." Water and Future, pp. 50-54.
13 
Lopez, M., Valero, S., Senabre, C., Aparichi, J. and Gabaldon, A. (2012). "Application of SOM neural networks to short-term load forecasting : The Spanish electricity market case study." Elsevier Electric Power Systems Research, Vol. 91, pp. 18-27.DOI
14 
Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D. and Veith, T. L. (2007). "Model evaluation guidelines for systematic quantification of accuracy in watershed simulations." ASABE., Vol. 50, No. 3, pp. 885-900.DOI
15 
Nanda, T., Sahoo, B. and Chatterjee, C. (2017). "Enhancing the applicability of Kohonen Self-Organizing Map (KSOM) estimator for gap-filling in hydrometeorological timeseries data." Journal of Hydrology, Vol. 549, pp. 133-147.DOI
16 
Seoul Metropolitan City (2015). Comprehensive Plan for Storm and Flood Damage Reduction (in Korean).
17 
Shin, S. Y., Yeo, C. G., Baek, C. H. and Kim, Y. J. (2005). "Mapping inundation areas by flash flood and developing rainfall standards for evacuation in urban settings." Journal of the Korean Association of Geographic Information Studies, Vol. 8, No. 4, pp. 71-80 (in Korean).
18 
Tsai, M. H., Sung, E. X. and Kang, S. C. (2016). "Data-driven flood analysis and decision support." Nat. Hazards Eearth Syst, Sci. Discuss., doi:10.5194/nhess-2016-141.DOI
19 
Wu, M. C., Lin, G. F. and Lin, H. Y. (2014). "Improving the forecasts of extreme streamflow by support vector regression with the data extracted by self-organizing map." Hydrological Process, Vol. 28, pp. 386-397.DOI