Human Mobility Prediction and Simulation After Natural Disasters: A Big Data Approach Using GPS Tracking and Machine Learning

This peer-reviewed journal article presents a computational framework for predicting and simulating population movements following large-scale natural disasters, developed through analysis of big and heterogeneous data from Japan. Using GPS records from 1.6 million anonymized users collected over three years, alongside earthquake intensity data, government declarations, news reports, and urban transportation network data, the authors […]

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