Groundwater level prediction using machine learning algorithms in a drought-prone area

Crops; Cultivation; Decision trees; Errors; Forecasting; Groundwater resources; Learning algorithms; Mean square error; Statistical tests; Support vector machines; Absolute error; Bangladesh; Correlation coefficient; Ground water level; Groundwater prediction; Locally weighted linear regression; Mea...

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Bibliographic Details
Main Authors: Pham Q.B., Kumar M., Di Nunno F., Elbeltagi A., Granata F., Islam A.R.M.T., Talukdar S., Nguyen X.C., Ahmed A.N., Anh D.T.
Other Authors: 57208495034
Format: Article
Published: Springer Science and Business Media Deutschland GmbH 2023
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Summary:Crops; Cultivation; Decision trees; Errors; Forecasting; Groundwater resources; Learning algorithms; Mean square error; Statistical tests; Support vector machines; Absolute error; Bangladesh; Correlation coefficient; Ground water level; Groundwater prediction; Locally weighted linear regression; Mean absolute error; Random tree; Root mean square errors; Squared errors; Groundwater