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Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

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Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

Improving Short-term Daily Streamflow Forecasting Using an Autoencoder Based CNN-LSTM Model

2024Water Resources ManagementJournal

10.1007/s11269-024-03937-2 Full text25 citations

Authors

12 authors across 8 institutions in 3 countries.

Umar Muhammad Mustapha KumsheFirst author
Zakariya Muhammad Abdulhamid
Baba Ahmad Mala
Tasiu Muazu
Abdullahi Uwaisu MuhammadCorresponding
- Federal University Dutse (NG)
Ousmane Sangary
Abdoul Fatakhou Ba
Sani Tijjani
- Kano State Polytechnic (NG)
Jibril Muhammad Adam
- Federal University Dutse (NG)
Mosaad Ali Hussein Ali
- Assiut University (EG)
Aliyu Bello
- Federal University Dutse (NG)
as printed: Aliyu Uthman Bello
Muhammad Muhammad BalaSenior author
- Kano State University of Technology (NG)

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Hydrological Forecasting Using AIlevel 3 · 1.00
Hydrology and Watershed Management Studieslevel 3 · 1.00
Energy Load and Power Forecastinglevel 3 · 1.00

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 9, 2026
2024 · Water Resources Management · 25 citations
https://openalex.org/W4401545075

Improving Short-term Daily Streamflow Forecasting Using an Autoencoder Based CNN-LSTM Model · Sankore