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River water level forecasting for flood warning system using deep learning long short-term memory network

Flood is considered chaotic, complex, volatile, and dynamics. Undoubtedly, its prediction is one of the most challenging tasks in time-series forecasting. Long short-term memory (LSTM) networks are a state of the art technique for time-series sequence learning. They are less commonly applied to the...

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Bibliographic Details
Main Authors:	Faruq, A., Abdullah, S. S., Marto, A., Bakar, M. A. A., Samin, Samin, Mubin, A.
Format:	Conference or Workshop Item
Language:	English
Published:	2020
Subjects:	T Technology (General)
Online Access:	http://eprints.utm.my/id/eprint/92492/1/ShahrumShahAbdullah2020_RiverWaterLevelForecastingForFloodWarning.pdf http://eprints.utm.my/id/eprint/92492/ http://dx.doi.org/10.1088/1757-899X/821/1/012026
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