Development of an intelligent system for early forecasting and modelling of flood situation on the example of the Republic of Bashkortostan using a proprietary machine and deep learning library

Author:

Palchevsky EvgenyORCID,Antonov Vyacheslav,Filimonov Nikolay,Rodionova LyudmilaORCID,Kromina Ludmila,Breikin Tim,Kuzmichev Artem,Pyatunin Alexander,Koryakin Valery

Funder

Ministry of Education and Science of the Russian Federation

Publisher

Elsevier BV

Reference55 articles.

1. «Flood 2.0» system. 2023 — https://elforecasting.com/?lang=eng.

2. «Flood» system – Dataset. 2023 - https://floodrb.ugatu.su/complete_no_null_water6.pdf.

3. «Flood» system. 2021 — https://floodrb.ugatu.su.

4. Abbaszadeh, P. et.al., 2022. Perspective on uncertainty quantification and reduction in compound flood modeling and forecasting. iScience. 105201.

5. Short-term rainfall forecasting using machine learning-based approaches of PSO-SVR, LSTM and CNN;Adaryani;J. Hydrol.,2022

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