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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.

Victor Amoako Temeng · Sankore

University of Mines and Technology

Victor Amoako Temeng

ORCID, self-asserted

ORCID 0000-0002-9536-0871

This profile carries an ORCID the researcher published on their own record — the strongest evidence available short of a human confirming it.

Publications

6

Citations

20

h-index

2

Computed over the works the graph holds, so it is a floor rather than a career figure.

i10-index

1

Works published 2022 onward have been swept for this country. Figures are complete within that window, to the extent the open indexes are.

Publications

6 works in the graph, newest first.

Optimisation of multilayer perceptron neural network using five novel metaheuristic algorithms for the prediction of wear of excavator bucket teeth
2025Knowledge-Based SystemsJournal11 citations10.1016/j.knosys.2025.113753
Enhanced site-specific constant estimation in blast-induced ground vibration models using stochastic fractal search optimisation
2025Mining Technology Transactions of the Institutions of Mining and MetallurgyJournalSenior author0 citations10.1177/25726668251359108
Application of artificial intelligence in predicting blast-induced ground vibration
2024Elsevier eBooksBook Chapter2 citations10.1016/b978-0-443-18764-3.00016-3
A Novel Approach in Predicting Dump Truck Tyre Life in a Mine Based on Multilayer Perceptron Neural Network Optimised with Particle Swarm Optimisation
2024Mining Metallurgy & ExplorationJournal1 citations10.1007/s42461-024-00954-y
A new synergetic model of neighbourhood component analysis and artificial intelligence method for blast-induced noise prediction
2023Modeling Earth Systems and EnvironmentJournal6 citations10.1007/s40808-023-01719-0
Appraisal of artificial intelligence techniques for the prediction of on-site dump truck tyre operating hours
2023International Journal of Mining and Mineral EngineeringJournal0 citations10.1504/ijmme.2023.133650