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- W3169155997 abstract "This paper proposes an approach to predicting the monthly natural streamflow at the Cahora Bassa dam, Mozambique, combining a Genetic Algorithm and an Extreme Learning Machine. The model uses measurements of the past monthly river flow, rainfall, temperature, and evaporation from the lake upstream of the dam to forecast stream flows three months ahead. A Genetic Algorithm automates the choice of the internal parameters of the Extreme Learning Machine. We analyzed the model’s forecasting ability using the past two, three, six, and nine months as input data. The efficiency of the proposed approach was assessed using four metrics. The results show that ELM produces precise estimates and outperforms other machine learning methods." @default.
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- W3169155997 date "2021-01-01" @default.
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- W3169155997 title "Automated Extreme Learning Machine to Forecast the Monthly Flows: A Case Study at Zambezi River" @default.
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- W3169155997 doi "https://doi.org/10.1007/978-3-030-71187-0_122" @default.
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