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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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What we cover

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.

ENHANCING ENERGY EFFICIENCY WITH AI: A REVIEW OF MACHINE LEARNING MODELS IN ELECTRICITY DEMAND FORECASTING

2023Engineering Science & Technology JournalJournalOpen access

10.51594/estj.v4i6.636 Full text94 citations

Authors

5 authors across 3 institutions in 2 countries.

Adebayo Olusegun AderibigbeFirst author
Emmanuel Chigozie Ani
Peter Efosa Ohenhen
Nzubechukwu Chukwudum Ohalete
Donald Obinna DaraojimbaSenior author
- Ahmadu Bello University (NG)

Fields

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

Energy Load and Power Forecastinglevel 3 · 0.98
Energy Efficiency and Managementlevel 3 · 0.93
Energy, Environment, and Transportation Policieslevel 3 · 0.93

Sources

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

openalexseen September 9, 2026
2023 · Engineering Science & Technology Journal · 94 citations
https://openalex.org/W4389454626

ENHANCING ENERGY EFFICIENCY WITH AI: A REVIEW OF MACHINE LEARNING MODELS IN ELECTRICITY DEMAND FORECASTING · Sankore