Water level prediction using various machine learning algorithms: A case study of Durian Tunggal river, Malaysia
A reliable model to predict the changes in the water levels in a river is crucial for better planning to mitigate any risk associated with flooding. In this study, six different Machine Learning (ML) algorithms were developed to predict the river's water level, on a daily basis based on collect...
Saved in:
Main Authors: | Ahmed, Ali Najah, Yafouz, Ayman, Birima, Ahmed H., Kisi, Ozgur, Huang, Yuk Feng, Sherif, Mohsen, Sefelnasr, Ahmed, El-Shafie, Ahmed |
---|---|
Format: | Article |
Published: |
Taylor & Francis Ltd
2022
|
Subjects: | |
Online Access: | http://eprints.um.edu.my/32716/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Water level prediction using various machine learning algorithms: a case study of Durian Tunggal river, Malaysia
by: Ahmed A.N., et al.
Published: (2023) -
Hybrid deep learning model for ozone concentration prediction: Comprehensive evaluation and comparison with various machine and deep learning algorithms
by: Yafouz, Ayman, et al.
Published: (2021) -
Comprehensive comparison of various machine learning algorithms for short-term ozone concentration prediction
by: Yafouz, Ayman, et al.
Published: (2022) -
Evaluation of deep learning algorithm for inflow forecasting: A case study of Durian Tunggal Reservoir, Peninsular Malaysia
by: Latif, Sarmad Dashti, et al.
Published: (2021) -
Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster
by: Afan, Haitham Abdulmohsin, et al.
Published: (2022)