Forecasting, clustering and patrolling criminal activities

Calvo, Hiram; Godoy-Calderón, Salvador; Moreno-Armendáriz, Marco A.; Martínez-Hernández, V.

doi:10.3233/ida-170883

Cited by 9 publications

(4 citation statements)

References 20 publications

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“…Recently, scholars have applied this method to different research fields. The application scope of spatiotemporal scanning statistics analysis started with the study of epidemic infectious diseases [81] and then extended to population mortality [82] and criminal acts [83]. The spatiotemporal scanning statistics method using SatScan has been introduced into geographical [84] and related research [85].…”

Section: Spatiotemporal Scanning Statistical Analysismentioning

confidence: 99%

Spatiotemporal Variation of Rural Vulnerability and Its Clustering Model in Guizhou Province

Zhou

Yang

2023

Land

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The vulnerability of China’s rural system is becoming increasingly obvious due to the multiple pressures of geological conditions and human interference. This study selected Guizhou Province to measure the degree of vulnerability and determine a rural system’s temporal and spatial characteristics. We select the county as the unit, build the vulnerability assessment of a rural system based on the three dimensions of exposure, sensitivity, and adaptability, and employ the combination weighting method. The final development indicator of the rural vulnerability measurement model was obtained using the Technique for Order Preference by Similarity to the Ideal Solution method. Further, SatScan v10.1 software was used for spatiotemporal scanning statistical analysis, and its clustering pattern was analyzed. Finally, visual analysis was conducted using ArcGIS 10.7 software. The results showed that exposure and sensitivity have an increasing fluctuation trend, while adaptability has a decreasing trend. The combined effect resulted in an increasing trend of vulnerability. The mean values of exposure, sensitivity, adaptation, and rural vulnerability in Yunyan are 0.906, 0.894, 0.772, and 1.028 higher than those in Nanming, i.e., 0.417, 0.426, 0.687, and 0.262, respectively. The vulnerability of the rural system shows a spatial pattern of “low in the middle and high on both sides,” with spatial clustering, and Guiyang and Zunyi are the cluster centers.

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Section: Spatiotemporal Scanning Statistical Analysismentioning

confidence: 99%

Spatiotemporal Variation of Rural Vulnerability and Its Clustering Model in Guizhou Province

Zhou

Yang

2023

Land

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“…A lot of police patrol routing strategies use historical crime or incident data to define patrol routes (Azimi & Bashiri, 2016;Calvo et al, 2017;Chen et al, 2017). However, priority codes have never been included in such a patrol strategy.…”

Section: Implementing Prioritization In Police Patrol Routing Strategiesmentioning

confidence: 99%

Hot spots and burning times: A spatiotemporal analysis of calls for service to establish police demand

et al. 2022

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“…To our knowledge, there have been only few studies about routing optimization in Mexico. In [6] and [7] authors presents a novel method using ant colonies for optimizing patrolling routes for personnel working in public security and the case study is municipality of Cuautitlán Izcalli in Mexico. Also in [8] authors design a routing planning software with the aim of distance minimization and travel cost for State of Puebla using dynamic programming and Floyd algorithm.…”

Section: Mexican Tspmentioning

confidence: 99%

The Mexican Magical Towns Traveling Salesman Problem: Preliminary Results

Gutiérrez¹,

Cruz²,

Calvo³

et al. 2017

RCS

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The Traveling Salesman Problem (TSP) is a classical NPhard combinatorial problem that has been intensively studied through several decades. A large amount of literature is dedicated to this problem. TSP can be directly applied to some real life problems, and to be generalized to some other set of important combinatorial problems. Nowadays, a large collection of TSP instances can be found such as TSPLIB and National TSP webpage, among others. In this paper we experiment with a different TSP instance, that is, a set of 111 Mexican towns (called Magical Towns), by applying five different algorithms: (1) Ant Colony Optimization, (2) Particle Swarm Optimization, (3) Greedy Metaheuristic (4) Lin-Kernighan and (5) Hybrid Metaheuristic. The best results were obtained by the hybrid metaheuristic, with a final cost function of 120.65.

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Forecasting, clustering and patrolling criminal activities

Cited by 9 publications

References 20 publications

Spatiotemporal Variation of Rural Vulnerability and Its Clustering Model in Guizhou Province

Spatiotemporal Variation of Rural Vulnerability and Its Clustering Model in Guizhou Province

Hot spots and burning times: A spatiotemporal analysis of calls for service to establish police demand

The Mexican Magical Towns Traveling Salesman Problem: Preliminary Results

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