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Influence of Varied Ambient Population Distribution on Spatial Pattern of Theft from the Person: The Perspective from Activity Space., , , , , и . ISPRS Int. J. Geo Inf., 11 (12): 615 (декабря 2022)Spatial Variation Relationship between Floating Population and Residential Burglary: A Case Study from ZG, China., , , , и . ISPRS Int. J. Geo Inf., 6 (8): 246 (2017)Explaining Theft Using Offenders' Activity Space Inferred from Residents' Mobile Phone Data., , , и . ISPRS Int. J. Geo Inf., 13 (1): 8 (декабря 2023)Modeling Spatial Effect in Residential Burglary: A Case Study from ZG City, China., , , , , и . ISPRS Int. J. Geo Inf., 6 (5): 138 (2017)Burglars blocked by barriers? The impact of physical and social barriers on residential burglars' target location choices in China., , , , и . Comput. Environ. Urban Syst., (2021)Journey-to-Crime Distances of Residential Burglars in China Disentangled: Origin and Destination Effects., , , , и . ISPRS Int. J. Geo Inf., 7 (8): 325 (2018)Contact-Fraud Victimization among Urban Seniors: An Analysis of Multilevel Influencing Factors., , , , , и . ISPRS Int. J. Geo Inf., 11 (3): 201 (2022)Comparison of Machine Learning Algorithms for Predicting Crime Hotspots., , , и . IEEE Access, (2020)Integrative Analysis of Spatial Heterogeneity and Overdispersion of Crime with a Geographically Weighted Negative Binomial Model., , , , и . ISPRS Int. J. Geo Inf., 9 (1): 60 (2020)Interpretable machine learning models for crime prediction., , , , , и . Comput. Environ. Urban Syst., (2022)