Published February 23, 2026 | Version v1
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Predicting Armed Conflict Probability: A Multi-Factor Machine Learning Approach

Authors/Creators

  • 1. Odessa National Polytechnic University

Description

Machine learning ensemble approach to predicting armed conflict using ACLED, UCDP, World Bank, SIPRI, and V-Dem data. Achieves 87.3% accuracy with XGBoost, Random Forest, and LSTM models.

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