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

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

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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...

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Bibliographic Details
Main Authors: Alawi, OA (Author), Al-Khafaji, ZS (Author), Chau, KW (Author), Deo, RC (Author), Elhakeem, M (Author), Farooque, AA (Author), Khedher, KM (Author), Kisi, O (Author), Melesse, AM (Author), Nejadhashemi, AP (Author), Nourani, V (Author), Qi, CC (Author), Shahid, S (Author), Singh, VP (Author), Tao, H (Author), Tiyasha, T (Author), Yaseen, ZM (Author), Zounemat-Kermani, M (Author)
Format: Article
Language:English
Published: 2021
Subjects:
Advanced computer aid
artificial intelligence models
COMPUTING METHODS
DATA-DRIVEN MODELS
INPUT SELECTION
LINEAR-MODELS
literature review
LOAD PREDICTION
LOESS PLATEAU
MATHEMATICAL-MODEL
NEURAL-NETWORK ANN
sediment transport modeling
SUPPORT VECTOR MACHINE
WAVELET TRANSFORM
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