Acknowledgement
본 결과물은 환경부의 재원으로 한국환경산업기술원의 가뭄대응 물관리 혁신 기술개발사업의 지원을 받아 연구되었습니다(2022003610002).
References
- Breiman, L. (1996). "Bagging predictors." Machine Learning, Vol. 24, pp. 124-140.
- Breiman, L. (2001). "Random forests." Machine Learning, Vol. 45, No. 1, pp. 5-32. https://doi.org/10.1023/A:1010933404324
- Jeon, H.B., Lee, Y.J., and Lee, J.D. (2001). "Effects of Prechlorination on diatoms coagulation." Journal of Korean Society on Water Environment, Vol. 17, No.3, pp. 347-355.
- Jung, S.H., Lee D.O., and Lee K.S. (2018). "Prediction of water level prediction of river water level using deep-lenaring open library." Journal of Korean Society of Hazard Mitigation, Vol. 18, No.1, pp.1-11. https://doi.org/10.9798/KOSHAM.2018.18.1.1
- Kang, K.W., Park, C.Y., and Kim, J.H. (1992). "Nonlinear prediction of streamflow by applying pattern recognition method." Journal of Korean Association of Hydrological Sciences, Vol.25. No.3, pp.105-113.
- Kim, D., Kim, J., Kwak, J., Necesito, I.V., Kim, J., and Kim, H.S. (2020). "Development of water level prediction models using deep neural network in mountain wetlands." Journal of Wetland Research, Vol. 22, No. 2, pp. 106-112.
- Kim, J.H. (1993). A study on hydrologic forecasting of stream flow by using artificial neural network. Ph.D. Dissertation, Inha University.
- Kumar, A.P.S., Sudheer, K.P., Jain, S.K., and Agarwal, P.K. (2005). "Rainfall runoff modeling using artificial neural networks: Comparison of network types." Hydrological Process Vol. 19, pp. 1277-1291. https://doi.org/10.1002/hyp.5581
- Lee, K.H., Kim, J.H., Lim, J.L., and Chae S.H. (2007). "Prediction models of residual chlorine in sediment basin to control prechlorination in water treatment plant" Journal of the Korean Society of Water and Wastewater, Vol. 21, No. 5, pp. 601-607.
- Lisboa, P.G.J. (1992). Neural networks: Current application. Chapman & Hall, London, pp. 5-6.
- Maneual, J.R., and Jean, B.S. (1999). "Assessing empirical linear and non-linear modeling of residual chlorine in urban drinking water systems." Environmental Modeling & Software, Vol. 14, No. 1, pp. 93-102.
- Qing, Z., and Stephen, J.S. (1999). "Real time water treatment process control with artificial neyral networks." Journal of Environmental Engineering, Vol. 125, No. 2, pp. 153-160. https://doi.org/10.1061/(ASCE)0733-9372(1999)125:2(153)
- Tiwari, M.K., and Chatterjee, C. (2010). "Development of an accurate and reliable hourly flood forecasting model using waveletbootstrap-ANN (WBANN) hybrid approach." Journal of Hydrology, Vol. 394, No. 3, pp. 458-470. https://doi.org/10.1016/j.jhydrol.2010.10.001
- Uber, J.G. (2003). Maintaining distribution system residuals through booster chlorination, IWA Publishing, London, UK, pp. 42-47.
- Yoon, J.Y., Byoun, S.J., and Choi, Y.S. (2001). "Importance of prechlorination practices and structures of clearwell in estimating disinfection capabilities in water treatment plants." Journal of Korean Society on Water Environment, Vol. 17, No. 3, pp. 327-337.