Evaluating Machine Learning Models for Rainfall Prediction: A Case Study of Nyando in Kenya-Reference-Cited by-同舟云学术

Evaluating Machine Learning Models for Rainfall Prediction: A Case Study of Nyando in Kenya

Published:2023-12-22 Issue: Volume:620 Page:264-271
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Container-title:2023 IEEE 15th International Conference on Computational Intelligence and Communication Networks (CICN)
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Author:

Lawal Ahmad¹,Yerima Suleiman Y.²,Olago Daniel O.³,Amingo Philip Omondi⁴,Kariuki Charles Wamagata⁵,Wang'ombe Wangari⁶,Olaka Lydia⁷,Obiero Linda⁸,Wandiga Shem Oyoo⁹

Affiliation:

1. Institute of Artificial Intelligence, De Montfort University,Leicester,United Kingdom

2. Cyber Technology Institute, De Montfort University,Leicester,United Kingdom

3. Institute for Climate Change & Adaptation, University of Nairobi,Nairobi,Kenya

4. IGAD Climate Prediction and Applications Centre (ICPAC),Department Climate Diagnostics and Predictions,Nairobi,Kenya

5. De Montfort University,Accounting and Finance Department,Leicester,United Kingdom

6. Leicester Castle Business School, De Montfort University,Leicester,United Kingdom

7. Technical University of Kenya,Dept. of Geoscience & the Environment,Nairobi,Kenya

8. University of Nairobi,Dept. of Earth & Climate Sciences,Nairobi,Kenya

9. Centre for Science and Technology Innovation,Managing Trustee,Nairobi,Kenya,00100

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10402119/10402128/10402269.pdf?arnumber=10402269

Reference27 articles.

1. Prediction of rainfall time series using modular soft computingmethods

2. A secondary-decomposition-ensemble learning paradigm for forecasting PM2.5 concentration

3. A SVR–ANN combined model based on ensemble EMD for rainfall prediction

4. Indian summer monsoon rainfall prediction using artificial neural network

5. Rainfall prediction: A comparative analysis of modern machine learning algorithms for time-series forecasting

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