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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2409.00359 |
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| _version_ | 1866912010140123136 |
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| author | Medel-Ramírez, Carlos Medel-López, Hilario |
| author_facet | Medel-Ramírez, Carlos Medel-López, Hilario |
| contents | The article focuses on the urgent issue of femicide in Veracruz, Mexico, and the development of the MFM_FEM_VER_CP_2024 model, a mathematical framework designed to predict femicide risk using fuzzy logic. This model addresses the complexity and uncertainty inherent in gender based violence by formalizing risk factors such as coercive control, dehumanization, and the cycle of violence. These factors are mathematically modeled through membership functions that assess the degree of risk associated with various conditions, including personal relationships and specific acts of violence. The study enhances the original model by incorporating new rules and refining existing membership functions, which significantly improve the model predictive accuracy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_00359 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Predicting Femicide in Veracruz: A Fuzzy Logic Approach with the Expanded MFM-FEM-VER-CP-2024 Model Medel-Ramírez, Carlos Medel-López, Hilario Artificial Intelligence 03E72, 91D10, 62P25, 91B76 G.1; G.3; I.2; I.6 The article focuses on the urgent issue of femicide in Veracruz, Mexico, and the development of the MFM_FEM_VER_CP_2024 model, a mathematical framework designed to predict femicide risk using fuzzy logic. This model addresses the complexity and uncertainty inherent in gender based violence by formalizing risk factors such as coercive control, dehumanization, and the cycle of violence. These factors are mathematically modeled through membership functions that assess the degree of risk associated with various conditions, including personal relationships and specific acts of violence. The study enhances the original model by incorporating new rules and refining existing membership functions, which significantly improve the model predictive accuracy. |
| title | Predicting Femicide in Veracruz: A Fuzzy Logic Approach with the Expanded MFM-FEM-VER-CP-2024 Model |
| topic | Artificial Intelligence 03E72, 91D10, 62P25, 91B76 G.1; G.3; I.2; I.6 |
| url | https://arxiv.org/abs/2409.00359 |