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Identifying areas vulnerable to homicide using multiple criteria analysis and spatial analysis

2020; Elsevier BV; Volume: 100; Linguagem: Inglês

10.1016/j.omega.2020.102211

1873-5274

Caroline Maria de Miranda Mota, Ciro José Jardim de Figueiredo, Débora Viana e Sousa Pereira,

Data Mining Algorithms and Applications

The decision-making process in public security is not an easy task. Several aspects must be considered, since resources are limited, whereas coverage should be extensive. Usually, preventative actions are allocated to areas that are more prone to violence, where criminal occurrences have happened in the recent past. In Brazil, such decisions are made in an ad-hoc way, considering only the knowledge of a specialist. This paper, however, aims to identify homicide vulnerability areas, taking into account the knowledge and preferences of an expert decision-maker under several criteria and data from a demographic census. Our model aggregates multiple-criteria analysis, based on Dominance-based Rough Set Approach, and spatial analysis, which consist of hot-spot analysis and local Moran's I. The model was applied in a neighbourhood of Brazil. The approach was able to highlight the problematic areas in the neighbourhood, and suggested locations where public policy and, consequently, limited resources should be allocated.