Mobile QR Code QR CODE : Journal of the Korean Society of Civil Engineers
1 
Brown, M. and Harris, C. (1994). Neuro-fuzzy adaptive modeling and control, Prentice Hall International (UK) Ltd. Hertfordshire, UK, p. 508.Brown, M. and Harris, C. (1994). Neuro-fuzzy adaptive modeling and control, Prentice Hall International (UK) Ltd. Hertfordshire, UK, p. 508.Google Search
2 
Carpenter, T. M., Georgakakos, K. P. and Sperfslage, J. A. (2001). “On the parametric and Nexrad-Radar sensitivities of a distributed hydrologic model suitable for operational use.” Journal of Hydrology, Vol. 253, pp. 169-193.10.1016/S0022-1694(01)00476-0Carpenter, T. M., Georgakakos, K. P. and Sperfslage, J. A. (2001). “On the parametric and Nexrad-Radar sensitivities of a distributed hydrologic model suitable for operational use.” Journal of Hydrology, Vol. 253, pp. 169-193.DOI
3 
Chaoulakou, A., Assimacopoulos, D. and Lekkas, T. (1999). “Forecasting daily maximum ozon concentration in the Athens basin.” Environmental Monitoring and Assessment, Vol 56, pp. 97-112.10.1023/A:1005943201063Chaoulakou, A., Assimacopoulos, D. and Lekkas, T. (1999). “Forecasting daily maximum ozon concentration in the Athens basin.” Environmental Monitoring and Assessment, Vol 56, pp. 97-112.DOI
4 
Choi, S.-Y. (2011). Real-time flood forecasting and inundation analysis in medium and small streams. Doctor Dissertation, Kyungpook National University (in Korean).Choi, S.-Y. (2011). Real-time flood forecasting and inundation analysis in medium and small streams. Doctor Dissertation, Kyungpook National University (in Korean).Google Search
5 
Gautam, D. K. and Holz, K. P. (2001). “Rainfall-runoff modeling using adaptive neuro-fuzzy systems.” Journal of Hydroinformatics, pp. 3-10.Gautam, D. K. and Holz, K. P. (2001). “Rainfall-runoff modeling using adaptive neuro-fuzzy systems.” Journal of Hydroinformatics, pp. 3-10.Google Search
6 
Imrie, C. E., Durucan, S. and Korre, A. (2000). “River flow prediction using artificial neural networks: generalisation beyond the calibration range.” Journal of Hydrology, Vol. 233, pp. 138-153.10.1016/S0022-1694(00)00228-6Imrie, C. E., Durucan, S. and Korre, A. (2000). “River flow prediction using artificial neural networks: generalisation beyond the calibration range.” Journal of Hydrology, Vol. 233, pp. 138-153.DOI
7 
Jain, A., Sudheer, K. P. and Srinivasulu, S. (2004). “Identification of physical processes inherent in artificial neural network rainfall- runoff models.” Hydrologic Process, Vol. 118, pp. 571-581.10.1002/hyp.5502Jain, A., Sudheer, K. P. and Srinivasulu, S. (2004). “Identification of physical processes inherent in artificial neural network rainfall- runoff models.” Hydrologic Process, Vol. 118, pp. 571-581.DOI
8 
Jang, J.-S. (1992). “Self-learning fuzzy controllers based on temporal backpropagation.” IEEE Trans Neural Netw, Vol. 3, No. 5, pp. 714-723.10.1109/72.159060Jang, J.-S. (1992). “Self-learning fuzzy controllers based on temporal backpropagation.” IEEE Trans Neural Netw, Vol. 3, No. 5, pp. 714-723.DOI
9 
Jeong, D.-K. and Lee, B.-H. (2009). “Development of urban flood water level forecasting model using regression method.” Journal of Korea Water Resources Association, Vol. 43, No. 2, pp. 221-231 (in Korean).10.3741/JKWRA.2010.43.2.221Jeong, D.-K. and Lee, B.-H. (2009). “Development of urban flood water level forecasting model using regression method.” Journal of Korea Water Resources Association, Vol. 43, No. 2, pp. 221-231 (in Korean).DOI
10 
Kim, K.-T., Kim, J.-H. and Choi, Y.-S. (2006). “Study of flood warning and forecasting in small to medium scale watershed.” Korea Water Resources Association Conf., pp. 1126-1130 (in Korean).Kim, K.-T., Kim, J.-H. and Choi, Y.-S. (2006). “Study of flood warning and forecasting in small to medium scale watershed.” Korea Water Resources Association Conf., pp. 1126-1130 (in Korean).Google Search
11 
Ko, Y.-J. (2001). The application of fuzzy neural network on the hourly river flow forecating. Master Dissertation, Chonnam National University. pp. 1-6, pp. 14-17 (in Korean).Ko, Y.-J. (2001). The application of fuzzy neural network on the hourly river flow forecating. Master Dissertation, Chonnam National University. pp. 1-6, pp. 14-17 (in Korean).Google Search
12 
Kurtulus, B. and Razack, M. (2009). “Modeling daily discharge responses of a large karstic aquifer using soft computing methods artificial neural network and neuro fuzzy.” Journal of Hydrology, Vol. 375, pp. 146-162.Kurtulus, B. and Razack, M. (2009). “Modeling daily discharge responses of a large karstic aquifer using soft computing methods artificial neural network and neuro fuzzy.” Journal of Hydrology, Vol. 375, pp. 146-162.Google Search
13 
Lohani, A. K., Kumar, R. and Singh, R. D. (2012). “Hydrological time series modeling: A Comparison Between Adaptive Neuro- Fuzzy, Neural Network And Autoregressive Techniques.” Journal of Hydrology, Vol. 442-443, pp. 23-35.10.1016/j.jhydrol.2012.03.031Lohani, A. K., Kumar, R. and Singh, R. D. (2012). “Hydrological time series modeling: A Comparison Between Adaptive Neuro- Fuzzy, Neural Network And Autoregressive Techniques.” Journal of Hydrology, Vol. 442-443, pp. 23-35.DOI
14 
Luk, K. C., Ball, J. E. and Sharma, A. (2001). “An application of artificial neural networks for rainfall forecasting.” Math Computer Model, Vol. 33, pp. 683-693.10.1016/S0895-7177(00)00272-7Luk, K. C., Ball, J. E. and Sharma, A. (2001). “An application of artificial neural networks for rainfall forecasting.” Math Computer Model, Vol. 33, pp. 683-693.DOI
15 
Nayak, P. C., Sudheer, K. P., Rangan, D. M. and Ramasastri, K. S. (2005). “Short-term flood forecasting with a neurofuzzy model.” Water Resources Research, Vol. 41, No. 4, W04004.10.1029/2004WR003562Nayak, P. C., Sudheer, K. P., Rangan, D. M. and Ramasastri, K. S. (2005). “Short-term flood forecasting with a neurofuzzy model.” Water Resources Research, Vol. 41, No. 4, W04004.DOI
16 
Ramirez, M. C. P., Velho, H. F. C. and Ferreira, N. J. (2005). “Artificial neural network technique for rainfall forecasting applied to the sao paulo region.” Journal of Hydrology, Vol. 301, pp. 146-162.10.1016/j.jhydrol.2004.06.028Ramirez, M. C. P., Velho, H. F. C. and Ferreira, N. J. (2005). “Artificial neural network technique for rainfall forecasting applied to the sao paulo region.” Journal of Hydrology, Vol. 301, pp. 146-162.DOI
17 
Schilling, K. E. and Wolter, C. F (2005). “Estimation of streamflow, baseflow and nitrate-nitrogen loads in Iwoa using multiple regression models.” Journal of American Water Resources Association, Vol. 41, No. 6, pp. 1333-1346.10.1111/j.1752-1688.2005.tb03803.xSchilling, K. E. and Wolter, C. F (2005). “Estimation of streamflow, baseflow and nitrate-nitrogen loads in Iwoa using multiple regression models.” Journal of American Water Resources Association, Vol. 41, No. 6, pp. 1333-1346.DOI
18 
Shin, S.-I. (2002). Study on forecasting flood discharge using neural network and neuro-fuzzy, Master Dissertation, Kyungil University (in Korean).Shin, S.-I. (2002). Study on forecasting flood discharge using neural network and neuro-fuzzy, Master Dissertation, Kyungil University (in Korean).Google Search
19 
Smith, J. and Eli, R. N. (1995). “Neural network models of the rainfall-runoff process.” Journal of Water Resources Planning and Management, ASCE, Vol. 121, pp. 499-508.10.1061/(ASCE)0733-9496(1995)121:6(499)Smith, J. and Eli, R. N. (1995). “Neural network models of the rainfall-runoff process.” Journal of Water Resources Planning and Management, ASCE, Vol. 121, pp. 499-508.DOI
20 
Sung, J.-Y. and Heo, J.-H. (2009). “Tributary flood forecasting using statistical analysis method.” Korea Water Resources Association Conf., pp. 1524-1527 (in Korean).Sung, J.-Y. and Heo, J.-H. (2009). “Tributary flood forecasting using statistical analysis method.” Korea Water Resources Association Conf., pp. 1524-1527 (in Korean).Google Search
21 
Talei, A., Chua, L. H. C. and Wong, S. W. (2010). “Evaluation of rainfall and discharge inputs used by adaptive network-based fuzzy inference systems (ANFIS) in rainfall-runoff modeling.” Journal of Hydrology, Vol. 391, Issues 3-4, pp. 248-262.10.1016/j.jhydrol.2010.07.023Talei, A., Chua, L. H. C. and Wong, S. W. (2010). “Evaluation of rainfall and discharge inputs used by adaptive network-based fuzzy inference systems (ANFIS) in rainfall-runoff modeling.” Journal of Hydrology, Vol. 391, Issues 3-4, pp. 248-262.DOI
22 
Tangborn, W. V. and Rasmussen, L. A. (1976). “Hydrology of north cascades region, washington-part 2: A Proposed Hydrometeorological Streamflow Prediction Method.” Water Resources Research, Vol. 12, pp. 203-216.10.1029/WR012i002p00203Tangborn, W. V. and Rasmussen, L. A. (1976). “Hydrology of north cascades region, washington-part 2: A Proposed Hydrometeorological Streamflow Prediction Method.” Water Resources Research, Vol. 12, pp. 203-216.DOI
23 
Wu, C. L., Chau, K. W. and Li, Y. S. (2008). “River stage prediction based on a distributed support vector regression.” Journal of Hydrology, Vol. 358, pp. 96-111.10.1016/j.jhydrol.2008.05.028Wu, C. L., Chau, K. W. and Li, Y. S. (2008). “River stage prediction based on a distributed support vector regression.” Journal of Hydrology, Vol. 358, pp. 96-111.DOI
24 
Yarar, M., Onucyildiz, M. and Copty, N. K. (2009). “Modelling level change in lakes using neuro fuzzy and artificial neural networks.” Journal of Hydrology, Vol. 365, pp. 329-334.10.1016/j.jhydrol.2008.12.006Yarar, M., Onucyildiz, M. and Copty, N. K. (2009). “Modelling level change in lakes using neuro fuzzy and artificial neural networks.” Journal of Hydrology, Vol. 365, pp. 329-334.DOI
25 
Yoon, Y.-N. and Wone, S.-Y. (1991). “A multiple regression model for the estimation of monthly runoff from ungaged watersheds.” Journal of Korean Association of Hydrological Sciences, Vol. 24, No. 3, pp.71-82 (in Korean).Yoon, Y.-N. and Wone, S.-Y. (1991). “A multiple regression model for the estimation of monthly runoff from ungaged watersheds.” Journal of Korean Association of Hydrological Sciences, Vol. 24, No. 3, pp.71-82 (in Korean).Google Search
26 
Yurekli, K., Kurung, A. and Ozturk, F. (2005). “Testing residuals of an ARIMA model on the cekerek stream watershed in turkey.” Turkish Journal of Engineering and Environmental Sciences, Vol. 29, pp. 61-74.Yurekli, K., Kurung, A. and Ozturk, F. (2005). “Testing residuals of an ARIMA model on the cekerek stream watershed in turkey.” Turkish Journal of Engineering and Environmental Sciences, Vol. 29, pp. 61-74.Google Search