Non-tuned machine learning approach for hydrological time series forecasting

• Main Authors: Yaseen, Zaher Mundher, Allawi, Mohammed Falah, Yousif, Ali A., Jaafar, Othman, Hamzah, Firdaus Mohamad, El-Shafie, Ahmed
• Format: Article
• Published: Springer Verlag (Germany) 2018
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.um.edu.my/20305/; https://doi.org/10.1007/s00521-016-2763-0

Stream-flow forecasting is a crucial task for hydrological science. Throughout the literature, traditional and artificial intelligence models have been applied to this task. An attempt to explore and develop better expert models is an ongoing endeavor for this hydrological application. In addition,...