Past, present and prospect of an Artificial Intelligence (AI) based model for sediment transport prediction
• The authors introduced a comprehensive state-of-the-art for AI-based sediment model. • The authors defined each data-driven of AI and AI-complementary model. • An assessment and evaluation have been carried out for the AI sediment models. • The comparison proved that AI-complementary model provide...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Afan, Haitham Abdulmohsin [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Schlagwörter: |
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| Umfang: |
12 |
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| Übergeordnetes Werk: |
Enthalten in: Neighborhood resources associated with frailty trajectories over time among community-dwelling older adults in China - Liu, Huiying ELSEVIER, 2021, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:541 ; year:2016 ; pages:902-913 ; extent:12 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.jhydrol.2016.07.048 |
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• The authors introduced a comprehensive state-of-the-art for AI-based sediment model. • The authors defined each data-driven of AI and AI-complementary model. • An assessment and evaluation have been carried out for the AI sediment models. • The comparison proved that AI-complementary model provided an accurate modelling. • Several recommended advanced techniques have been proposed for future research. |
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• The authors introduced a comprehensive state-of-the-art for AI-based sediment model. • The authors defined each data-driven of AI and AI-complementary model. • An assessment and evaluation have been carried out for the AI sediment models. • The comparison proved that AI-complementary model provided an accurate modelling. • Several recommended advanced techniques have been proposed for future research. |
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