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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.

AI Enabled Energy Demand Forecasting with LSTM Neural Networks on Smart Grid Data

2025International Journal of Future Engineering InnovationsJournalOpen access

10.54660/ijfei.2025.2.6.01-08 Full text0 citations

Authors

8 authors across 7 institutions in 2 countries.

Samuel Ayanwunmi OlanrewajuFirst author
- Yaba College of Technology (NG)
Hanafi Musa Olayinka
Chijioke Cyriacus Ekechi
Adeolu Aremu Samuel
- Federal University of Agriculture, Abeokuta (NG)
Adeolu Aremu Samuel
- Federal University of Agriculture, Abeokuta (NG)
Oluwatoyin Olawale Akadiri
Victor Ikechukwu Stephen
- Michael Okpara University of Agriculture (NG)
Abdulraheem Adedayo ThanniSenior author
- University of Lagos (NG)

Fields

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

Energy Load and Power Forecastinglevel 3 · 0.96
Traffic Prediction and Management Techniqueslevel 3 · 0.01
Smart Grid Energy Managementlevel 3 · 0.01

Sources

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

openalexseen September 9, 2026
2025 · International Journal of Future Engineering Innovations · 0 citations
https://openalex.org/W4415763215

AI Enabled Energy Demand Forecasting with LSTM Neural Networks on Smart Grid Data · Sankore