Data-driven Inflow Prediction
Data-Driven Inflow Prediction is a predictive modeling approach that belongs to the class of reservoir inflow forecasting methods and is distinguished by its reliance on empirical data and statistical or machine learning techniques to estimate inflow without explicit representation of hydrological processes.
217
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12.4K
Citations
671
Authors
333
Institutions
Publications per year
2017–2026
136
Parents
217
Mohammad Valipour, Mohammad Ebrahim Banihabib, Seyyed Mahmood Reza Behbahani · Journal of Hydrology · 2012 · 844 citations
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333

University of Tehran
Tehran, Iran
10 h-index
17 publications
3K citations

National Taiwan University
Taipei, Taiwan
9 h-index
26 publications
1.2K citations
University of Tabriz
Tabriz, Iran
6 h-index
8 publications
288 citations
University of Malaya
Kuala Lumpur, Malaysia
6 h-index
7 publications
257 citations

Indian Institute of Technology Bombay
Mumbai, India
5 h-index
11 publications
382 citations

Universiti Tenaga Nasional
Kuala Selangor, Malaysia
4 h-index
3 publications
119 citations

National University of Malaysia
Bangi, Malaysia
4 h-index
7 publications
337 citations
Wuhan University
Wuhan, China
4 h-index
16 publications
556 citations
1–8 of 333
23 publications · 3.3K citations
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19 publications · 1.3K citations
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10 publications · 323 citations
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10 publications · 403 citations
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6 publications · 563 citations
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