Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting
Flood, which is the most common natural disaster that occurs worldwide, causes massive casualties and damages to people and environment respectively. Hence, flood prediction is integral to minimise the damage and loss of life, while simultaneously aiding the government authorities and even the pr...
Saved in:
Main Author: | Loh, Eng Chuen |
---|---|
Format: | Thesis |
Language: | English English English |
Published: |
2021
|
Subjects: | |
Online Access: | http://eprints.uthm.edu.my/6319/1/24p%20LOH%20ENG%20CHUEN.pdf http://eprints.uthm.edu.my/6319/2/LOH%20ENG%20CHUEN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/6319/3/LOH%20ENG%20CHUEN%20WATERMARK.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Flood analysis of Sg. Galas at Dabong, Kelantan by using the HEC-HMS software
by: Ahmad, Noor Aliza
Published: (2004) -
Water level forecasting model using improved artificial neural network architecture
by: Muhammad @ S. A. Khushren, Sulaiman
Published: (2012) -
Flood forecasting for Melaka using arima and nar modelling methods
by: Wong, Wei Ming
Published: (2022) -
Geospatial approach for flood vulnerability assessment in Kelantan River Basin, Malaysia
by: Tam, Tze Huey
Published: (2022) -
Rainfall-runoff model calibration and daily streamflow simulation for an ungauged catchment
by: Mohd., Zamri
Published: (2000)