Incorporating park events into crime hotspot prediction on street networks: A spatiotemporal graph learning approach-Reference-Cited by-同舟云学术

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Incorporating park events into crime hotspot prediction on street networks: A spatiotemporal graph learning approach

Published:2023-11 Issue: Volume:148 Page:110886
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Hakyemez Tugrul Cabir,Badur Bertan

Publisher

Elsevier BV

Subject

Software

Reference66 articles.

1. How do residential burglars select target areas A new approach to the analysis of criminal location choice;Bernasco;Br. J. Criminol.,2005

2. Do street robbery location choices vary over time of day or day of week? A test in Chicago;Bernasco;J. Res. Crime. delinquency,2017

3. Prospective hot-spotting: the future of crime mapping;Bowers;Br. J. Criminol.,2004

4. Courier routing and assignment for food delivery service using reinforcement learning;Bozanta;Comput. Ind. Eng.,2022

5. Environmental Criminology;Brantingham,1981

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhanced Public Safety through LSTM-Based Spatio-Temporal Crime Analytics;2023 International Conference on Emerging Research in Computational Science (ICERCS);2023-12-07

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