1- Alizadeh, A. (2004). Principle of applied hydrology, 17th Ed., Imam Reza University, Mashhad, Iran. (In Persian)
2- The OFDA/CRED International Disaster Database. (2009). <www.em-dat.net> (Dec. 5, 2009).
3- I.R. Iran Metorological Organistaion. (2006). <www.weather.ir> (Jan. 15, 2007).
4- Farokhnia, A., Morid, S., and Ghaemi, H. (2008). “Inyestigation on large scale climatiologically signals to predict long term drough.” 3rd Proc. Iranian Water Resources Management Conferece, Tabriz University, Tabriz. (In Persian)
5- Anvari, S. (2008). “Increse artificial models to predict reiver discharge using distributed climatologically and snow surface data.” MSc. Thesis, Hydraulic Structures, Tarbiat Modares University, Tehran, Iran. (In Persian)
6- Bagherzadeh Chehreh, K. (2005). “Evaluation of meteorological signals on forecasting in Tehran province using artificial neural network.” M.S. Thesis, Hydraulic Structures, Tarbiat Modares University, Tehran, Iran.
7- Hosseinpour Niknam, H., Azhdary Moghaddam, M., and Khosravi, M. (2010). “Drought forecasting using adaptive neuro-fuzzy inferece system (ANFIS) and teleconnections patterns, case study: Zahedan.” 4th International Congress of Islamic World Geographers (ICIWG), University of Sistan and Balouchestan, Zahedan, Iran. (In Persian)
8- Poustizadeh, N., Samani, J.M.V., and Dezfuli, A.K. (2008). “River flow forecasting using fuzay inference system.” Iran, Water Resources Research, 4 (2), 23-34. (In Persian)
9- Bacanli, U., Firat, M., and Dikbas, F. (2008). “Adaptive neuro-fuzzy inference system (ANFIS) for drought forecasting.” Stoch. Environ. Res. Risk Assess, 23 (8), 1143-1154.
10- Zounemat Kermani, M., and Teshnehlab, M. (2008). “Using adaptive neuro-fuzzy inference system for hydrological time series prediction.” Applied Soft Computing, 8(2), 928-936.
11- Morid, S., Smakhtin, V., and Bagherzadeh, K. (2007). “Drought forecasting using artificial neural networks and time series of drought indices.” International J. of Climatology, 27, 2103-2111.
12- Karamouz, M., Tabesh, M., Nazif, S., and Moridi, A. (2005). “Estimation of hydraulic pressure in water network using artificial nevral network and fuzzy logic.” J. of Water and Wastewater, 53, 3-14. (In Persian)
13- Saadatpour, M., Afshar, A., and Bozorg Haddad, O. (2006). “Fuzzy simulation- optimization model for waste load allocation.” J. of Water and Wastewater, 56, 2-10. (In Persian)
14- Nayak, P., Sudheer, K., Rangan, D., and Ramasa, K. (2004). “A neuro-fuzzy computing technique for modeling hydrological time series.” J. of Hydrology, 291, 52-66.
15- Pongracz, R., Bogardi, I., and Ducksteinc, L. (1999). “Application of fuzzy rule-based modeling technique to regional drought.” J. of Hydrology, 224, 100-114.
16- McKee, T.B., Doesken, N.J., and Kleist, J. (1993). “The relationship of drought frequency and duration to time steps.” Preprints, 8th Conference on Applied Climatology, Anaheim, California, 179-184.
17- Raziei, T., Daneshkar Arasteh, P., Akhtari, R., and Saghafian, B. (2007). “Investigation of meteorological droughts in the Sistan and Balouchestan province, using the standardized precipitation index and Markov Chain model.” Iran Water Resources Reserch, 3 (1), 25-35. (In Persian)
18- Khosravi, M. (2004). “Study of relation between large scale Northern Hemiphere atmospheric circulation Pattern with sistan and Balouchestan naaual drought.” Irannian J. of Geography and Development, 3, 167-188. (In Persian)
19- Hosseinpour Niknam, H. (2009). “Drough forecasting using adaptive neuro-fuzzy inference system (ANFIS) and climate indices case study, Zahedan, Iran.” M.Sc. Thesis, University of Systan and Balouchestan, Zahedan. (In Persian)
21- Jang, J.-S.R.(1993). “ANFIS: Adaptive network based fuzzy inference system.” IEEE Transactions on Systems, Man and Cybernetics, 23 (3), 665-683.
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