Data reformation – A novel data processing technique enhancing machine learning applicability for predicting streamflow extremes

Tran, Vinh Ngoc; Ivanov, Valeriy Y.; Kim, Jongho

doi:10.1016/j.advwatres.2023.104569

Advances in Water Resources

2023

DOI: 10.1016/j.advwatres.2023.104569

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Data reformation – A novel data processing technique enhancing machine learning applicability for predicting streamflow extremes

Vinh Ngoc Tran,

Valeriy Y. Ivanov,

Jongho Kim

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Cited by 4 publications

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Data reformation – A novel data processing technique enhancing machine learning applicability for predicting streamflow extremes

Cited by 4 publications

References 99 publications

Data-Driven Dam Outflow Prediction Using Deep Learning with Simultaneous Selection of Input Predictors and Hyperparameters Using the Bayesian Optimization Algorithm

Data-Driven Dam Outflow Prediction Using Deep Learning with Simultaneous Selection of Input Predictors and Hyperparameters Using the Bayesian Optimization Algorithm

Multiple data-driven approaches for estimating daily streamflow in the Kone River basin, Vietnam

A framework on utilizing of publicly availability stream gauges datasets and deep learning in estimating monthly basin-scale runoff in ungauged regions

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