Results 11 to 20 of about 5,507,676 (170)
Graph Representation Learning for Street-Level Crime Prediction
ISPRS International Journal of Geo-InformationIn contemporary research, the street network emerges as a prominent and recurring theme in crime prediction studies. Meanwhile, graph representation learning shows considerable success, which motivates us to apply the methodology to crime prediction ...
Haishuo Gu, Jinguang Sui, Peng Chen
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Crime Geographical Displacement: Testing Its Potential Contribution to Crime Prediction
ISPRS International Journal of Geo-Information, 2019 Crime geographical displacement has been examined in many Western countries. However, little is known about its existence, distribution, and potential predictive ability in large cities in China.
Zengli Wang +3 more
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Examining Deep Learning Architectures for Crime Classification and Prediction
Forecasting, 2021 In this paper, a detailed study on crime classification and prediction using deep learning architectures is presented. We examine the effectiveness of deep learning algorithms in this domain and provide recommendations for designing and training deep ...
Panagiotis Stalidis +2 more
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Complexity, 2022 The crime is difficult to predict; it is random and possibly can occur anywhere at any time, which is a challenging issue for any society. The study proposes a crime prediction model by analyzing and comparing three known prediction classification ...
Muzammil Khan, Azmat Ali, Yasser Alharbi
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IEEE Access, 2021 Ensemble learning method is a collaborative decision-making mechanism that implements to aggregate the predictions of learned classifiers in order to produce new instances. Early analysis has shown that the ensemble classifiers are more reliable than any
Sapna Singh Kshatri +5 more
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Dynamic transfer learning with co-occurrence-guided multi-source fusion for urban spatio-temporal crime prediction [PDF]
Frontiers in Big DataSpatio-temporal crime prediction is crucial for optimizing police resource allocation but faces challenges including data sparsity, which hinders models from extracting effective patterns and limits robustness—and the underutilization of cross-type crime
Chen Cui +4 more
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Urban Crime Risk Prediction Using Point of Interest Data
ISPRS International Journal of Geo-Information, 2020 Geographical information systems have found successful applications to prediction and decision-making in several areas of vital importance to contemporary society.
Paweł Cichosz
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Grid-Based Crime Prediction Using Geographical Features
ISPRS International Journal of Geo-Information, 2018 Machine learning is useful for grid-based crime prediction. Many previous studies have examined factors including time, space, and type of crime, but the geographic characteristics of the grid are rarely discussed, leaving prediction models unable to ...
Ying-Lung Lin +2 more
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Electronic coverage as of Jan. 12, 2011: 2006-; Vol. for 2006 published as part of: Annual report / Crime Victims Section.; Vol. for 2007-2008 issued by the Ohio Victims of Crime Compensation Program, Crime Victims Compensation Section; v.
Ohio Victims of Crime Compensation Program.
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ST3DNetCrime: Improved ST-3DNet Model for Crime Prediction at Fine Spatial Temporal Scales
ISPRS International Journal of Geo-Information, 2022 Crime prediction is crucial for sustainable urban development and protecting citizens’ quality of life. However, there exist some challenges in this regard. First, the spatio-temporal correlations in crime data are relatively complex and are heterogenous
Qifen Dong +4 more
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