Modeling the fluctuations of groundwater level by employing ensemble deep learning techniques

Modeling the fluctuations of groundwater level by employing ensemble deep learning techniques

This study proposes two techniques: Deep Learning (DL) and Ensemble Deep Learning (EDL) to predict groundwater level (GWL) for five wells in Malaysia. Two scenarios were proposed, scenario-1 (S1): GWL from 4 wells was used as inputs to predict the GWL in the fifth well and scenario-2 (S2): time seri...

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Bibliographic Details
Main Authors: Haitham Abdulmohsin Afan, Ahmedbahaaaldin Ibrahem Ahmed Osman, Yusuf Essam, Ali Najah Ahmed, Yuk Feng Huang, Ozgur Kisi, Mohsen Sherif, Ahmed Sefelnasr, Kwok-wing Chau, Ahmed El-Shafie
Format: Article
Language:English
Published: Taylor & Francis Group 2021-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
groundwater level prediction
deep learning model
ensemble deep learning model
malaysia
Online Access:http://dx.doi.org/10.1080/19942060.2021.1974093

Internet

http://dx.doi.org/10.1080/19942060.2021.1974093

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