طراحی مدل هوشمند پیش‌بینی و مدیریت سیلاب شهری مبتنی بر داده‌های هواشناسی ماهواره‌ای و الگوریتم‌های یادگیری ماشین با رویکرد کاهش خسارات زیرساختی در کلان‌شهرها

Mosavi A, Ozturk P, Chau KW. Flood prediction using machine learning models: Literature review. Water. 2018;10(11):1536.

Sit MA, Demiray BZ, Xiang Z, Ewing GJ, Sermet Y, Demir I. A comprehensive review of deep learning applications in hydrology and water resources. Water Science and Technology. 2020;82(12):2635-2670.

Chen Y, Zhou H, Zhang H, Du G, Zhou J. Urban flood susceptibility assessment using integrated machine learning models and remote sensing data. Journal of Hydrology. 2021;598:126458.

Shen Y, Chen X, Chen J, Lu P. Satellite precipitation products for hydrological applications in flood forecasting: A review. Remote Sensing. 2022;14(9):2050.

Kim J, Han D, Kim HS. Improving urban flood prediction using real-time rainfall radar and machine learning approaches. Journal of Hydroinformatics. 2021;23(5):1142-1159.

Xiang Z, Demir I. Distributed long-term hourly streamflow predictions using deep learning – A case study for State of Iowa. Environmental Modelling & Software. 2020;131:104761.

Kabir S, Patidar S, Xia X, Liang Q, Neal J, Pender G. A deep convolutional neural network model for rapid inundation mapping using UAV and satellite imagery. Journal of Hydrology. 2020;590:125481.

Bentivoglio R, Isufi E, Jonkman SN, Taormina R. Deep learning methods for flood mapping from remote sensing data: A review. Remote Sensing. 2022;14(21):5401.

Guo Y, Wang Y, Niu J, Wang L. Urban flood risk assessment based on machine learning and GIS techniques under extreme rainfall events. Science of the Total Environment. 2022;806:150455.

Nachappa TG, Piralilou ST, Gholamnia K, Ghorbanzadeh O, Blaschke T. Flood susceptibility mapping using machine learning algorithms. Geomatics, Natural Hazards and Risk. 2020;11(1):2372-2401.

Ahmadisharaf E, Kalyanapu AJ, Chung ES. Evaluating the effects of inundation duration and velocity on selection of flood management alternatives using multi-criteria decision making. Water. 2021;13(3):354.

Janizadeh S, Avand M, Jaafari A, Van Phong T, Bayat M, Ahmadisharaf E, et al. Prediction success of machine learning methods for flash flood susceptibility mapping in different climates. Science of the Total Environment. 2021;701:134728.

Costache R, Hong H, Pham QB. Comparative assessment of the flash-flood potential within small mountain catchments using bivariate statistics and machine learning models. Science of the Total Environment. 2020;711:134514.

Rahmati O, Falah F, Naghibi SA, Biggs T, Soltani M, Deo RC, et al. Land subsidence modelling using tree-based machine learning algorithms in urban areas. Geoscience Frontiers. 2021;12(6):101250.

Hu P, Zhang Q, Shi P, Chen B, Fang J. Flood-induced mortality across the globe: Spatiotemporal pattern and influencing factors. Science of the Total Environment. 2018;643:171-182.

Yariyan P, Avand M, Janizadeh S, Van Phong T, Nguyen HD, Costache R, et al. Spatial modeling of flood susceptibility using machine learning models in Northern Iran. Remote Sensing. 2020;12(14):2236.