Spatio-Temporal Prediction of Baltimore Crime Events Using CLSTM Neural Networks-Reference-Cited by-同舟云学术

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Spatio-Temporal Prediction of Baltimore Crime Events Using CLSTM Neural Networks

Published:2020 Issue: Volume:8 Page:209101-209112
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Esquivel Nicolas,Nicolis Orietta^ORCID,Peralta Billy^ORCID,Mateu Jorge^ORCID

Funder

Spanish

Chilean Fondecyt

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09252093.pdf?arnumber=9252093

Cited by 28 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. Neural networks for intelligent multilevel control of artificial and natural objects based on data fusion: A survey;Information Fusion;2024-10

2. Research on the method of predicting the trend of criminal activities based on time series analysis from the perspective of criminal procedure law;Applied Mathematics and Nonlinear Sciences;2024-01-01

3. Developing Predictive Models for Smart Policing Based on Baltimore’s Crime and Product Price Correlation;Lecture Notes in Networks and Systems;2024

4. Visual Knowledge Discovery and Criminal Justice. Insights from a Computational Crime Analysis Research;Studies in Computational Intelligence;2024

5. 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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