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Predicting Conflict Events in West Africa Using Climate, Socio-Economic, and Population Data

Domaine:

peace and securitysocioeconomicclimate

Type de record:

paperproject
Créateur:
ADE
Éditeur:
Zenodo
Hôte:avatar

This study presents a data-driven approach to predicting conflict events in West Africa by combining climate data, socio-economic indicators, and population metrics. Using a Random Forest Regressor, the model identifies key drivers of conflict, including population size and unemployment. Predictions for 2024 and 2027 provide actionable insights for policymakers and humanitarian organizations.

The research demonstrates how artificial intelligence can support decision-making, resource allocation, and early intervention strategies, contributing to the broader goal of promoting peace and stability in the region.

Keywords: conflict prediction, machine learning, West Africa, socio-economic indicators, climate, population, dashboard

Visit

doi.org

Tags

conflict predictionmachine learningWest Africasocio-economic indicatorsclimate, populationdashboard

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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