Results 11 to 20 of about 9,406 (253)
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
exaly +3 more sources
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 +2 more
exaly +3 more sources
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 ...
Liang-Chih Yu
exaly +3 more sources
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
doaj +1 more source
Artificial intelligence & crime prediction: A systematic literature review
Social Sciences and Humanities Open, 2022 The security of a community is its topmost priority; hence, governments must take proper actions to reduce the crime rate. Consequently, the application of artificial intelligence (AI) in crime prediction is a significant and well-researched area.
Fatima Dakalbab +5 more
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Journal of Pharmaceutical Negative Results, 2022 Abstract: Crimes are treacherous social problems which are faced worldwide. It is the most serious and predominant issue of our society. It affects various key features bound to the society and an individual’s life like the quality of life, reputation, economic growth and societal safety.
Amshu S Gajendra, Aruna S, Malini R
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OPTIMIZED FEATURES AND DEEP LEARNING BASED CRIME TRENDS PREDICTION
ICTACT Journal on Soft Computing, 2021 Crime Prediction is an effort of determining future crime with the intention of diminishing them. Post-analysis of the data from past events, Crime prediction forecasts the future crime on the basis of time and location.
J Jeyaboopathiraja, G Maria Priscilla
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Machine learning in crime prediction
Journal of Ambient Intelligence and Humanized Computing, 2023 AbstractPredicting crimes before they occur can save lives and losses of property. With the help of machine learning, many researchers have studied predicting crimes extensively. In this paper, we evaluate state-of-the-art crime prediction techniques that are available in the last decade, discuss possible challenges, and provide a discussion about the ...
Karabo Jenga, Cagatay Catal, Gorkem Kar
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SARIMA-GRU Crime Prediction Model Based on Nonlinear Combination of BP Neural Network
Taiyuan Ligong Daxue xuebao, 2023 Aiming at the problems that the current crime prediction model can not capture the composite characteristics of crime sequence data or respond to the dynamic changes of the environment in time, a SARIMA-GRU crime prediction model based on nonlinear ...
Shengchang ZHAI +4 more
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