River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network

• Main Authors: Zanial W.N.C.W., Malek M.B.A., Reba M.N.M., Zaini N., Ahmed A.N., Sherif M., Elshafie A.
• Other Authors: 57205239441
• Format: Article
• Published: Springer Science and Business Media Deutschland GmbH 2024
• Subjects: ANN; Hybrid CS-ANN; Hydropower Plant; River flow; Malaysia; Biomimetics; Hydroelectric power; Hydroelectric power plants; Learning algorithms; Machine learning; Neural networks; Optimization; Rivers; Stream flow; Artificial neural network modeling; Case-studies; Hybrid CS-artificial neural network; Hydropower plants; Machine learning methods; Prediction-based; River flow prediction; Stand -alone; Statistical indices; algorithm; artificial neural network; hydroelectric power plant; machine learning; precipitation intensity; prediction; river flow; Mean square error
• Institution: Universiti Tenaga Nasional

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 the river...