Predicting Femicide in Veracruz: A Fuzzy Logic Approach with the Expanded MFM-FEM-VER-CP-2024 Model

TL;DR

This paper introduces an advanced fuzzy logic model to predict femicide risk in Veracruz, Mexico, by formalizing complex risk factors and improving predictive accuracy through refined rules and membership functions.

Contribution

The study develops the MFM-FEM-VER-CP-2024 model, enhancing femicide risk prediction by integrating new rules and refined membership functions within a fuzzy logic framework.

Findings

Improved predictive accuracy of femicide risk model

Effective formalization of risk factors like coercive control and dehumanization

Enhanced model performance with new rules and refined membership functions

Abstract

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.