Browsing Faculty of Science & Technology (FST) by Subject "general additive model; drought risk management; early warning system; model selection; overfitting; cross-validation"
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A mixed model approach to vegetation condition prediction using artificial neural networks (ANN): case of Kenya’s Operational Drought Monitoring
(MDPI, 2019-05-08)Droughts, with their increasing frequency of occurrence, especially in the Greater Horn of Africa (GHA), continue to negatively affect lives and livelihoods. For example, the 2011 drought in East Africa caused massive ...