Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions

• Main Authors: Tao, Hai, Al-Khafaji, Zainab S., Qi, Chongchong, Zounemat-Kermani, Mohammad, Kisi, Ozgur, Tiyasha, Tiyasha, Chau, Kwok Wing, Nourani, Vahid, Melesse, Assefa M., Elhakeem, Mohamed, Farooque, Aitazaz Ahsan, Nejadhashemi, A. Pouyan, Khedher, Khaled Mohamed, Alawi, Omer A., Deo, Ravinesh C., Shahid, Shamsuddin, Singh, Vijay P., Yaseen, Zaher Mundher
• Format: Article
• Language: English
• Published: Taylor and Francis Ltd. 2021
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/id/eprint/95590/1/ShamsuddinShahid2021_ArtificialIntelligenceModelsforSuspended.pdf; http://eprints.utm.my/id/eprint/95590/; http://dx.doi.org/10.1080/19942060.2021.1984992

River sedimentation is an important indicator for ecological and geomorphological assessments of soil erosion within any watershed region. Sediment transport in a river basin is therefore a multifaceted field yet being a dynamic task in nature. It is characterized by high stochasticity, non-linearit...