Use of Artificial Neural Networks in Determining Domestic Violence Predictors

This paper aims to determine the predictors of violence against women by their partners, according to the National Survey of Demography and Health - ENDS - Colombia, 2017 using artificial neural networks. The results indicate that the best forecasting model found is the artificial neural network, perceptron model, multilayer associative memory with a hidden layer of 20 units, through functions of sigmoidal activation and sum of square of the error as error function. The ten main explanatory variables are: respect for human rights of the partner, respect for wishes, love expressed by the partner, a history of domestic violence, engaging in joint decision making, decision of contraceptive use, number of connections (partners) of the respondent, decision-making at the financial level, correction of children behavior, and decisions regarding women's health at home.

• Autores: silva d, jesus g; GUERRA ALEMAN, ERICK; Camargo ACUÑA, Genesis Yulie; REDONDO BILBAO, OSMAN ENRIQUE; Hernandez-P, Hugo; León Castro, Bella; Arrieta Meléndez, Pedro; Neira Rodado, Dionicio
• Tipo de recurso: http://purl.org/coar/resource_type/c_816b
• Fecha de publicación: 2019
• Institución: Corporación Universidad de la Costa
• Repositorio: REDICUC - Repositorio CUC
• Idioma: eng
• OAI Identifier: oai:repositorio.cuc.edu.co:11323/5578
• Acceso en línea: https://hdl.handle.net/11323/5578; https://repositorio.cuc.edu.co/
• Palabra clave: Artificial neural network; Multilayer perceptron; Domestic violence
• Rights: openAccess
• License: CC0 1.0 Universal