Designing Deep-Based Learning Flood Forecast Model With ConvLSTM Hybrid Algorithm

Designing Deep-Based Learning Flood Forecast Model With ConvLSTM Hybrid Algorithm

Efficient, robust, and accurate early flood warning is a pivotal decision support tool that can help save lives and protect the infrastructure in natural disasters. This research builds a hybrid deep learning (ConvLSTM) algorithm integrating the predictive merits of Convolutional Neural Network (CNN...

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Bibliographic Details
Main Authors: Mohammed Moishin, Ravinesh C. Deo, Ramendra Prasad, Nawin Raj, Shahab Abdulla
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
ConvLSTM
deep learning
flood forecasting
flood index
flood risk management
Online Access:https://ieeexplore.ieee.org/document/9378529/

Internet

https://ieeexplore.ieee.org/document/9378529/

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