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Comparing Machine-Learning Models for Drought Forecasting in Vietnam's Cai River Basin
2018
Polish Journal of Environmental Studies
Drought occurs throughout the world, affecting people more than any other major natural hazards -especially in the agriculture industry. An effective and timely monitoring system is required to mitigate the impacts of drought. Meanwhile, extreme learning machine (ELM), online sequential extreme learning machine (OS-ELM), and self-adaptive evolutionary extreme learning machine (SADE-ELM) are rarely applied as the alternative drought-forecasting tools in the meantime. The present study aims to
doi:10.15244/pjoes/80866
fatcat:jj6a3ocpafbs3edwkto6dkp2eq