River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network
Abstract One of the largest hydropower facilities currently in operation in Malaysia is the Terengganu hydroelectric facility. As a result, for hydropower generation to be sustainable, future water availability in hydropower plants must be known. Therefore, it is necessary to precisely estimate how...
Main Authors: | Wan Norsyuhada Che Wan Zanial, Marlinda Binti Abdul Malek, Mohd Nadzri Md Reba, Nuratiah Zaini, Ali Najah Ahmed, Mohsen Sherif, Ahmed Elshafie |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2022-12-01
|
Series: | Applied Water Science |
Subjects: | |
Online Access: | https://doi.org/10.1007/s13201-022-01830-0 |
Similar Items
-
Rainfall-runoff modelling based on global climate model and tropical rainfall measuring mission (GCM -TRMM): A case study in Hulu Terengganu catchment, Malaysia
by: Wan Norsyuhada Che Wan Zanial, et al.
Published: (2023-05-01) -
River flow prediction based on improved machine learning method: Cuckoo search-artificial neural network
by: Che Wan Zanial, Wan Norsyuhada, et al.
Published: (2023) -
Methods for Hydropower Discharge Prediction: A Review
by: Nurul Najwa Anuar, et al.
Published: (2021-02-01) -
Corrigendum to “Rainfall-runoff modelling based on global climate model and tropical rainfall measuring mission (GCM -TRMM): A case study in Hulu Terengganu catchment, Malaysia” [Heliyon 9, Issue 5, May 2023, Article e15740]
by: Wan Norsyuhada Che Wan Zanial, et al.
Published: (2024-02-01) -
Evaluation of Empirical Modelling Techniques for the Estimation of Sediment Amount in Rivers
by: Başak GÜVEN, et al.
Published: (2016-12-01)