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        Using Random Forest Machine learning to estimate the impact of hydrological drought on the shipping industry

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        Publication date
        2022
        Author
        Ven, Jordy van de
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        Summary
        Hydrological droughts can have severe impacts on water levels in a river and consequentially also on shipping. Traditionally research on the impact of hydrological drought is done by means of numerical modeling. In this study a machine learning approach was used, to investigate the viability of data driven approaches in drought estimations. It was found that random forest machine learning is a promising tool that can be used to study the impact of hydrological drought.
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        https://studenttheses.uu.nl/handle/20.500.12932/41461
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