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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.

Optimizing artificial neural network models for predicting the irrigation potential of groundwater sources

2026Journal of Statistical Sciences and Computational IntelligenceJournalOpen access

10.64497/jssci.148 Full text0 citations

Authors

5 authors across 5 institutions in 2 countries.

Ifeoluwa AdebanjoFirst author
- Ladoke Akintola University of Technology (NG)
A. A. Adegbola
- Ladoke Akintola University of Technology (NG)
as printed: Adedayo Ayodele Adegbola
Olatunji Sunday Olaniyan
- Ladoke Akintola University of Technology (NG)
Musa Umar Kolo
O.O. FadipeSenior author
- Osun State University (NG)
as printed: Olusola Olayemi Fadipe

Fields

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

Groundwater and Isotope Geochemistrylevel 3 · 0.45
Groundwater and Watershed Analysislevel 3 · 0.12
Hydrological Forecasting Using AIlevel 3 · 0.11

Sources

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

openalexseen September 9, 2026
2026 · Journal of Statistical Sciences and Computational Intelligence · 0 citations
https://openalex.org/W7154274703

Optimizing artificial neural network models for predicting the irrigation potential of groundwater sources · Sankore