Enhancing short-term crime prediction with human mobility flows and deep learning architectures
Published in EPJ Data Science, 2022
We developed and evaluated novel deep learning architectures that combine spatial, temporal, and mobility features to improve short-term crime prediction accuracy, demonstrating significant improvements over traditional approaches.
Recommended citation: Wu, J., Abrar, S.M., Awasthi, N., Frias-Martinez, E. & Frias-Martinez, V. (2022). Enhancing short-term crime prediction with human mobility flows and deep learning architectures. EPJ Data Science, 11(1), p.53.
Recommended citation: Wu, J., Abrar, S.M., Awasthi, N., Frias-Martinez, E. & Frias-Martinez, V. (2022). Enhancing short-term crime prediction with human mobility flows and deep learning architectures. EPJ Data Science, 11(1), p.53.
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