ستاری، م.، رضازاده جودی، ع. (1397). مدل‌سازی رواناب ماهانه با استفاده از روش‌های داده‌کاوی بر اساس الگوریتم‌های انتخاب ویژگی. حفاظت منابع آب و خاک، 7(4)، 39-54.
سلگی، ا.، زارعی، ح.، شهنی دارابی، م.، و علیدادی ده کهنه، ص. (1397). کاربرد مدل‌های برنامه‌ریزی بیان ژن و ماشین بردار رگرسیونی جهت مدل‌سازی و پیش‌بینی بارش ماهانه. تحقیقات کاربردی علوم جغرافیایی، 18(50)، 91-103.
عساکره، ح.، و بیات، ع. (1392). تحلیل روند و چرخه ویژگی‌های بارندگی سالانه زنجان. جغرافیا و برنامه‌ریزی، 17(45)، 121-142.
قاجارنیا، ن.، لیاقت، ع.، و دانش کارآراسته، پ. (1393). صحت‌سنجی داده‌های بارندگی ایستگاه‌های غیرثبات سازمان هواشناسی و تماب در حوضه آبریز دریاچه ارومیه. حفاظت منابع آب و خاک، 4(1)، 109-91.
کاظم‌زاده، م.، ملکیان، ا.، مقدم‌نیا، ع.، و خلیقی، ش. (1398). ارزیابی اثرات تغییر اقلیم بر خصوصیات هیدرولوژیکی حوزه آبخیز (مطالعه موردی: حوزه آبخیز آجی چای). علوم و مهندسی آبخیزداری ایران، 13(45)، 1-11.
Aftab, S., Ahmad, M., Hameed, N., Bashir, M.S., Ali, I., & Nawaz, Z. (2018). Rainfall prediction in Lahore City using data mining techniques. International Journal of Advanced Computer Science and Applications, 9(4), 254-260.
Amiri, S.S., Mottahedi, M., & Asadi, S. (2015). Using multiple regression analysis to develop energy consumption indicators for commercial buildings in the US. Energy and Buildings, 109, 209-216.
Andrews, D.F. (1974). A robust method for multiple linear regression. Technometrics, 16(4), 523-531.
Asakareh, H., & Bayat, A. (2013). The analysis of the trend and the cycles of annual precipitation characteristics of Zanjan. Geography and Planning, 17(45), 121-142 (in Persian).
Baeriswyl, P.A., & Rebetez, M. (1997). Regionalization of precipitation in Switzerland by means of principal component analysis. Theoretical and Applied Climatology, 58(1), 31-41.
Balafoutis, C.J. (1991). Principal component analysis of Albanian rainfall (No. RefW-15-14613). Aristotle University of Thessaloniki.
Bărbulescu, A., & Băutu, E. (2009). ARIMA models versus gene expression programming in precipitation modeling. Pp. 112-117, Recent Advances in Evolutionary Computing.
Cattell, R.B. (1966). The Scree test for the number of factors. Multivariate Behavioral Research, 1(2), 245-276.
Dutta, P.S., & Tahbilder, H. (2014). Prediction of rainfall using data mining technique over Assam. Indian Journal of Computer Science and Engineering (IJCSE), 5(2), 85-90.
Ferreira, C. (2002). Gene expression programming in problem solving. Pp. 635-653, In: Soft computing and industry (), Springer, London.
Ghajarnia, N., Liaghat, A., & Arasteh, P.D. (2015). Comparison and evaluation of high-resolution precipitation estimation products in Urmia Basin-Iran. Journal of Water and Soil Resources Conservation, 4(1), 91-109 (in Persian).
Hasan, N., Nath, N.C., & Rasel, R.I. (2015). A support vector regression model for forecasting rainfall. 2nd International Conference on Electrical Information and Communication Technologies (EICT), Pp. 554-559.
Jolliffe, I.T. (1993). Principal component analysis: a beginner's guide-II. Pitfalls, myths and extensions. Weather, 48(8), 246-253.
Jolliffe, I.T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2065), 20150202.
Kazemzadeh, M., Malekian, A., Moghaddamnia, A. R., & Sigaroudi, K. (2019). Evaluation of Climate Change Impacts on Hydrological Characteristics of Watershed (Case study: Aji-Chai Watershed). Iranian Journal of Watershed Management Science and Engineering, 13(45), 1-11 (in Persian).
Krzywinski, M., & Altman, N. (2015). Multiple linear regression. Nature Methods, 12(12), 1103-1104.
Lu, K., & Wang, L. (2011). A novel nonlinear combination model based on support vector machine for rainfall prediction. 4th International Joint Conference on Computational Sciences and Optimization, Pp. 1343-1346.
Mehr, A.D. (2018). Month ahead rainfall forecasting using gene expression programming. American Journal of Environmental Sciences, 1(2), 63-70.
Mirabbasi, R., Kisi, O., Sanikhani, H., & Gajbhiye Meshram, S. (2019). Monthly long-term rainfall estimation in Central India using M5Tree, MARS, LSSVR, ANN and GEP models. Neural Computing and Applications, 31(10), 6843-6862.
Nolan, B.T., Fienen, M.N., & Lorenz, D.L. (2015). A statistical learning framework for groundwater nitrate models of the Central Valley, California, USA. Journal of Hydrology, 531, 902-911.
Pai, P.F., & Hong, W.C. (2007). A recurrent support vector regression model in rainfall forecasting. Hydrological Processes, 21(6), 819-827.
Piña-Monarrez, M.R., & Ortiz-Yañez, J.F. (2015). Weibull and lognormal Taguchi analysis using multiple linear regression. Reliability Engineering & System Safety, 144, 244-253.
Preacher, K.J., Curran, P.J., & Bauer, D.J. (2006). Computational tools for probing interactions in multiple linear regression, multilevel modeling, and latent curve analysis. Journal of Educational and Behavioral Statistics, 31(4), 437-448.
Sattari, M. T. & Rezazadeh Judi, A. (2018). Monthly runoff modeling using data mining methods based on feature selection algorithms. Protection of Water and Soil Resources, 7(4), 39-54 (in Persian).
Solgi, A., Zarei, H., Shahni, D.M., & Alidadi, D.K.S. (2018). Application of gene expression programming and support vector regression models to modeling and prediction monthly precipitation. Journal of Geographical Sciences, 18(50), 91-103 (in Persian).
Sneyers, R., Vandiepenbeeck, M., & Vanlierde, R. (1989). Principal component analysis of Belgian rainfall. Theoretical and applied Climatology. 39(4),199-204.
Stathis, D., & Myronidis, D. (2009). Principal component analysis of precipitation in Thessaly region (Central Greece). Global Network of Environmental Science and Technology Journal, 11(4), 467-476.
Steiner, D. (1965). A Multivariate Statistical Approach to Climatic Regionalization and Classification. EJ Brill.
Sureh, F.S., Sattari, M.T., & İrvem, A. (2019). Estimation of monthly precipitation based on machine learning methods by using meteorological variables. Mustafa Kemal Üniversitesi Tarım Bilimleri Dergisi, 24, 149-154.
Swain, S., Patel, P., & Nandi, S. (2017). A multiple linear regression model for precipitation forecasting over Cuttack district, Odisha, India. the 2nd International Conference for Convergence in Technology, Pp. 355-357.
Tripathi, S., Srinivas, V.V., & Nanjundiah, R.S. (2006). Downscaling of precipitation for climate change scenarios: a support vector machine approach. Journal of Hydrology, 330(3-4), 621-640.
Vapnik, V.N., & Chervonenkis, A.Y. (2015). On the uniform convergence of relative frequencies of events to their probabilities. Pp. 11-30, In: Measures of complexity.
Whetton, P.H. (1988). A synoptic climatological analysis of rainfall variability in southeastern Australia. Journal of Climatology, 8(2), 155-177.
Wilks, D.S. (2011). Statistical methods in the atmospheric sciences (Vol. 100). Academic press.
Willmott, C.J. (1978). P-mode principal components analysis, grouping and precipitation regions in California. Archives for Meteorology Geophysics and Bioclimatology Series B Theoretical and Applied Climatology, 26(4), 277-295.
Zaw, W.T., & Naing, T.T. (2008). Empirical statistical modeling of rainfall prediction over Myanmar. International Journal of Computer and Information Engineering, 2(10), 3418-3421.
)
