Artificial intelligence models for suspended river sediment prediction: state-of-the art, modeling framework appraisal, and proposed future research directions
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...
Main Authors: | Alawi, O.A (Author), Al-Khafaji, Z.S (Author), Chau, K.-W (Author), Deo, R.C (Author), Elhakeem, M. (Author), Farooque, A.A (Author), Khedher, K.M (Author), Kisi, O. (Author), Melesse, A.M (Author), Nourani, V. (Author), Pouyan Nejadhashemi, A. (Author), Qi, C. (Author), Shahid, S. (Author), Singh, V.P (Author), Tao, H. (Author), Tiyasha, T. (Author), Yaseen, Z.M (Author), Zounemat-Kermani, M. (Author) |
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Format: | Article |
Language: | English |
Published: |
Taylor and Francis Ltd.
2021
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Series: | Engineering Applications of Computational Fluid Mechanics
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Subjects: | |
Online Access: | View Fulltext in Publisher View in Scopus |
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