Sustainable flood risk assessment using deep learning-based algorithms with a blockchain technology

The couplings of convolutional neural networks (CNN) with random forest (RF), support vector machine (SVM), long short-term memory (LSTM), and extreme gradient boosting (XGBoost) ensemble algorithms were used to construct novel ensemble computational models (CNN-LSTM, CNN-XG, CNN-SVM, and CNN-RF) fo...

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Vydané v:	Geocarto international Ročník ahead-of-print; číslo ahead-of-print; s. 1 - 29
Hlavní autori:	Mia, Md. Uzzal, Rahman, Mahfuzur, Elbeltagi, Ahmed, Abdullah-Al-Mahbub, Md, Sharma, Gitika, Islam, H. M. Touhidul, Pal, Subodh Chandra, Costache, Romulus, Islam, Abu Reza Md. Towfiqul, Islam, Md Monirul, Chen, Ningsheng, Alam, Edris, Washakh, Rana Muhammad Ali
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Taylor & Francis 12.08.2022
Predmet:	Blockchain deep learning algorithm flash floods relief sustainable development
ISSN:	1010-6049, 1752-0762
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