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...
Saved in:
Main Authors: | , , , , , |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
2020
|
Subjects: | |
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 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|