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Application of augmented bat algorithm with artificial neural network in forecasting river inflow in Malaysia

Hydrologists rely extensively on anticipating river streamflow (SF) to monitor and regulate flood management and water demand for people. Only a few simulation systems, where previous techniques failed to anticipate SF data quickly, let alone cost-effectively, and took a long time to execute. The ba...

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Bibliographic Details
Main Authors:	Wee W.J., Chong K.L., Ahmed A.N., Malek M.B.A., Huang Y.F., Sherif M., Elshafie A.
Other Authors:	57226181151
Format:	Article
Published:	Springer Science and Business Media Deutschland GmbH 2024
Subjects:	Artificial neural network Bat meta-heuristic algorithm Streamflow forecasting Uncertainty analysis Malaysia Flood control Forecasting Heuristic algorithms Heuristic methods Neural networks Stream flow Artificial neural network modeling Bat algorithms Flood waters Meta-heuristics algorithms Performance River inflow Study areas algorithm artificial neural network forecasting method inflow river flow streamflow uncertainty analysis
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