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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.

Relative Predictive Accuracy of Machine Learning-Enhanced Long Memory Volatility Models for Modeling Nigeria Energy Data

2026International Journal of Science and Management Studies (IJSMS)JournalOpen access

10.51386/25815946/ijsms-v9i1p129 Full text0 citations

Authors

9 authors across 2 institutions in 1 country.

Awogbemi Clement AdeyeyeFirst author
Deebom Zorle Dum
- Rivers State University (NG)
OyoweiEsueze Augustine
Oloda Festus Smart Sunday
Okwuoza Sylvester Orobosa
Florence Ale
Olowu Rafiu Abiodun
Osamo Caleb Kehinde
- Veritas University (NG)
Attah Eleojo VincentSenior author
- Veritas University (NG)

Fields

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

Market Dynamics and Volatilitylevel 3 · 0.72
Energy Load and Power Forecastinglevel 3 · 0.04
Stock Market Forecasting Methodslevel 3 · 0.03

Sources

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

openalexseen September 9, 2026
2026 · International Journal of Science and Management Studies (IJSMS) · 0 citations
https://openalex.org/W7141568306

Relative Predictive Accuracy of Machine Learning-Enhanced Long Memory Volatility Models for Modeling Nigeria Energy Data · Sankore