مقایسة روش‌های نروفازی و SCS در اولویت‌بندی زیرحوضه‌های آبخیز به منظور اجرای اقدامات آبخیزداری (مطالعة موردی: حوضة آبخیز طالقان)

[1] Aqil, M., Kita, I., Yano, A. and Nishiyama, S. (2007a). Analysis and prediction of flow from local source in a river basin using a Neuro-fuzzy modeling tool, Journal of Environmental Management, 85, 215-223.

[2] Aqil, M., Kita, I., Yano, A. and Nishiyama, S. (2007b). A comparative study of artificial neural networks and neuro-fuzzy in continuous modeling of the daily and hourly behaviour of runoff, Journal of Hydrology, 337, 22-34.

[3] Arbind, K., Verma, M., Rajesh, K. and Mahana, K. (2010). Evaluation of HEC-HMS and WEPP for simulating watershed runoff using remote sensing and geographical information system, Paddy Water Environ, 8, 131-144.

[4] Bhola, K., Punit and Singh, A. (2010). Rainfall-runoff modeling of river Kosi using SCS-CN method and ANN, Bachelor thesis, Rourkela.

[5] Chen, S., Lin, Y., Chang, L. and Chang, F. (2006). The strategy of building a flood forecast model by neuro fuzzy network, Hydrological processes, 20, 1525-1540.

[6] Fathabadi, A. (2007). River flow prediction by Neurofuzzy and time series analysis, M.Sc. thesis, Tehran University.

[7] Firat, M. and Güngör, M. (2007). River flow estimation using adaptive neuro fuzzy inference system, Mathematics and Computers in Simulation, 75, 87-96.

[8] Foody, G., Ghoneim, E. and Arnell, W. (2004). Predicting Location Sensitive to Flash Flooding in Arid Environment, Journal of Hydrology, 292, 48-58.

[9] Han, J. (2002). Application of artificial neural networks for flood warning systems, Ph.D. thesis, North Carolina University.

[10] Jahangir, A. (2004). Rainfall-runoff simulation with artificial neural network (ANN) and HEC-HMS model in Kardeh watershed, M.Sc. thesis, Sari University.

[11] Jahangir, A., Raeini, M. and Ahmadi, M.Z. (2008). Rainfall-runoff simulation with artificial neural network (ANN) and HEC-HMS model in Kardeh watershed, Water and Soil Journal, 22, 72-84.

[12] Jang, J.S. (1993). ANFIS: adaptive-network-based fuzzy inference system, IEEE Transactions on Systems, Management and Cybernetics, 23, 665-685.

[13] Khedri-Tajan, B. (2003). Application of fuzzy logic in prioritizing watershed management operations in the Shahrestanak watershed, M.Sc. thesis, Tarbiat Modares, 110pp.

[14] Khosravi, M. (2008). Flood forecasting by artificial neural networks and emprical equations (Case study: Taleghan watershed), M.Sc. thesis, Tehran University.

[15] Khosroshahi, M. and Saghafian, B. (2003). Determination of sub-basins Participation in flood density, Pajouhesh va Sazandegi, 16, 67-75.

[16] Kisi, O., Haktanir, T., Ardiclioglu, M., Ozturk, O., Yalcin, E. and Uludag, S. (2009). Adaptive neuro-fuzzy computing technique for suspended sediment estimation, Advances in Engineering Software, 40, 438-444.

[17] Klausmeyer, K. (2005). Effects of climate change on the hydrology of upper Alameda Creek, M.Sc. thesis, University of California.

[18] Kurtulus, B. and Razack, M. (2010). Modeling daily discharge responses of a large karstic aquifer using soft computing methods: Artificial neural network and neuro-fuzzy, Journal of Hydrology, 381, 101-111.

[19] Mahdavi, M. (2002). Applied Hydrology, 2^nd Volume, University of Tehran Press.

[20] Nayak, P.C., Sudheer, K.P., Rangan, D.M. and Ramasastri, K.S. (2004). A neuro-fuzzy computing technique for modeling hydrological time series, Journal of Hydrology, 291, 52-66.

[21] Roughani, M., Ghafouri, M. and Tabatabaei, M. (2007). An innovative methodology for the prioritization of sub-catchments for flood control, International Journal of Applied Earth Observation and Geoinformation, 9, 79-87.

[22] Salajeghe, A. and Fathabadi, A. (2009). Suspended sediment evaluation by fuzzy logic and artifial network, Iranian Journal of Natural Resources (Range and Watershed Management), 62, 271-282.

[23] Talei, A., Chua, L.H. and Quek, C. (2010). A novel application of a neuro-fuzzy computational technique in event-based rainfall-runoff modeling, Expert Systems with Applications, 37, 7456-7468.

[24] Trahan, M. (2005). Hydrology model of the silver river watershed Baraga country, M.Sc. thesis, Michigan Technological University.

[25] USACE (2000). HEC-HMS Technical Manual, Hydrologic Engineering Center, Davis.

[26] USDI (1975). Water measurement manual, United States government printing office, bureau of reclamation, Washington.

[27] Vafakhah, M. (2008). Simulating snow discharge by artifical neural network, fuzzy logic and measurment data of snow in Taleghan watershed, Ph.D. thesis, Tehran University.

[28] Vafakhah, M. (2012). Application of artificial neural networks and adaptive neuro-fuzzy inference system models to short-term streamflow forecasting, Canadian Journal of Civil Engineering, 39, 402-414.