A Decision Support Tool Based on WSN and ML Models for Adaptation and Management of Groundwater Resources in Sub-Saharan Africa-Reference-Cited by-同舟云学术

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A Decision Support Tool Based on WSN and ML Models for Adaptation and Management of Groundwater Resources in Sub-Saharan Africa

Published:2023-09-20 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE AFRICON
language:
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Author:

Kombo Omar Haji¹,Kumaran Santhi²,Ndashimye Emannuel³

Affiliation:

1. The State University of Zanzibar,Department of Computer and Information Technology,Zanzibar,Tanzania

2. The Copperbelt University,Department of Computer Engineering,Kitwe,Zambia

3. College of Engineering Carnegie Mellon University Africa,Kigali,Rwanda

Funder

Copperbelt University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10293181/10293212/10293319.pdf?arnumber=10293319

Reference31 articles.

1. Quantifying increased groundwater demand from prolonged drought in the East African Rift Valley

2. Global Groundwater Sustainability, Resources, and Systems in the Anthropocene

3. Reassessing the projections of the World Water Development Report

4. Monitoring socio-climatic interactions to prioritise drinking water interventions in rural Africa

5. Uncertainty Quantification in Machine Learning Modeling for Multi-Step Time Series Forecasting: Example of Recurrent Neural Networks in Discharge Simulations

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