حسن زاده ی، آقاخانی افشار ا ح،" استفاده از مدل MIROC- ESM در بررسی شرایط هیدرو- اقلیمی حوضه آبخیز کوچک مقیاس تحت اثر تغییر اقلیم"، نشریه مهندسی عمران و محیط زیست دانشگاه تبریز، 1398، 94، 59-47.
نورانی و، رنجبر س، توتونچی ف، "بررسی تغییرات فرآینـدهای هیدرولوژیکی با استفاده از معیاره موجک- آنتروپی مطالعه موردی: دریاچه ارومیه"، نشریه مهندسی عمران و محیط زیست دانشگاه تبریز، 1394، 80، 86-75.
Abrahart RJ, Anctil F, Coulibaly P, Dawson Ch, Mount NJ, See L, Shamseldin A, Solomatine D, Toth E, Wilby LR, “Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting”, Progress in Physical Geography, 2012, 36, 480-513.
Addison PS, “The illustrated wavelet transform handbook: introductory theory and applications in science, engineering, medicine and finance”, CRC Press, 2002.
Antar MA, Elassiouti I, Alam MN, “Rainfall-runoff modeling using artificial neural networks technique: a Blue Nile catchment case study”, Hydrological Processes, 2006, 20, 1201-1216.
Chang FJ, Tsai MJ, “A nonlinear spatio-temporal lumping of radar rainfall for modeling multi-step-ahead inflow forecasts by data-driven techniques”, Journal of Hydrology, 2016, 535, 256-269.
Dinu C, Drobot R, Pricop C, Blidaru TV, “Flash-flood modelling with artificial neural networks using radar rainfall estimates”, Mathematical Modelling in Civil Engineering, 2017, 13, 10-20.
Grossmann A, Morlet J, “Decomposition of hardy function into square integrable wavelets of constant shape”, Journal on Mathematical Analysis, 1984, 154, 723-736
Khanghah TR, Nourani V, Parhizkar M, Sharghi E, “Application of information content to extract wavelet-based feature of rainfall–runoff process”, In Proceedings of the 12th WSEAS International Conference on Applied Computer Science, WSEAS, Greece, 2012, 148-153.
Kim T, Valdes JB, “Nonlinear model for drought forecasting based on a conjunction of wavelet transforms and neural networks”, Journal of Hydrologic Engineering, 2003, 8, 319-328.
Nourani V, Hosseini Baghanam A, Adamowski J, Kisi O, “Applications of hybrid wavelet-Artificial Intelligence models in hydrology: A review”, Journal of Hydrology, 2014, 514, 358-377.
Nourani V, Kisi Ö, Komasi M, “Two hybrid Artificial Intelligence approaches for modelling rainfall-runoff process”, Journal of Hydrology, 2011, 402, 41-59.
Sharghi E, Nourani V, Najafi H, Molajou A, “Emotional ANN (EANN) and wavelet-ANN (WANN) approaches for Markovian and seasonal based modeling of rainfall-runoff process”, Water Resources Management, 2018, 32, 3441-56.
Tankersley C, Graham W, Hatfield K, “Comparison of univariate and transfer function models of groundwater fluctuations”, Water Resources Reasearch, 1993, 29, 3517-3533.
Xie JX, Cheng CT, Chau KW, Pei YZ, “A hybrid adaptive time-delay neural network model for multi-step-ahead prediction of sunspot activity”, International Journal of Environment and Pollution, 2006, 28, 364-381.
Yang JS, Yu SP, Liu GM, “Multi-step-ahead predictor design for effective long-term forecast of hydrological signals using a novel wavelet neural network hybrid model”, Hydrology and Earth System Sciences, 2013, 17, 4981-4993.
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