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, pe...
- 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:
- http://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
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| dc.title.spa.fl_str_mv |
Use of Artificial Neural Networks in Determining Domestic Violence Predictors |
| title |
Use of Artificial Neural Networks in Determining Domestic Violence Predictors |
| spellingShingle |
Use of Artificial Neural Networks in Determining Domestic Violence Predictors Artificial neural network Multilayer perceptron Domestic violence |
| title_short |
Use of Artificial Neural Networks in Determining Domestic Violence Predictors |
| title_full |
Use of Artificial Neural Networks in Determining Domestic Violence Predictors |
| title_fullStr |
Use of Artificial Neural Networks in Determining Domestic Violence Predictors |
| title_full_unstemmed |
Use of Artificial Neural Networks in Determining Domestic Violence Predictors |
| title_sort |
Use of Artificial Neural Networks in Determining Domestic Violence Predictors |
| dc.creator.fl_str_mv |
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 |
| dc.contributor.author.spa.fl_str_mv |
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 |
| dc.subject.spa.fl_str_mv |
Artificial neural network Multilayer perceptron Domestic violence |
| topic |
Artificial neural network Multilayer perceptron Domestic violence |
| description |
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. |
| publishDate |
2019 |
| dc.date.accessioned.none.fl_str_mv |
2019-11-05T21:18:27Z |
| dc.date.available.none.fl_str_mv |
2019-11-05T21:18:27Z |
| dc.date.issued.none.fl_str_mv |
2019 |
| dc.type.spa.fl_str_mv |
Pre-Publicación |
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http://purl.org/coar/resource_type/c_816b |
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Text |
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info:eu-repo/semantics/preprint |
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info:eu-repo/semantics/acceptedVersion |
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http://purl.org/coar/resource_type/c_816b |
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acceptedVersion |
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http://hdl.handle.net/11323/5578 |
| dc.identifier.instname.spa.fl_str_mv |
Corporación Universidad de la Costa |
| dc.identifier.reponame.spa.fl_str_mv |
REDICUC - Repositorio CUC |
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https://repositorio.cuc.edu.co/ |
| url |
http://hdl.handle.net/11323/5578 https://repositorio.cuc.edu.co/ |
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Corporación Universidad de la Costa REDICUC - Repositorio CUC |
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eng |
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eng |
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CC0 1.0 Universal |
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http://creativecommons.org/publicdomain/zero/1.0/ |
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info:eu-repo/semantics/openAccess |
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CC0 1.0 Universal http://creativecommons.org/publicdomain/zero/1.0/ http://purl.org/coar/access_right/c_abf2 |
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openAccess |
| dc.publisher.spa.fl_str_mv |
Universidad de la Costa |
| institution |
Corporación Universidad de la Costa |
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silva d, jesus g1f6ba3473d23b4212c7f525ad6a550bcGUERRA ALEMAN, ERICK21ef0d3cbb9bf0d1181f1e1b1982f413Camargo ACUÑA, Genesis Yulie7363d46d8e3677f7fd2f75fa3aac7f19REDONDO BILBAO, OSMAN ENRIQUEdb2199af6787280002e379cd07972f7aHernandez-P, Hugoa6c875b0d0f83c92784cb2bc077e535fLeón Castro, Bellab357bc2a4996b707e65437633e8a22a5Arrieta Meléndez, Pedro2cd30e3365620b165704c2b2f9da4506Neira Rodado, Dionicio3be1ac9c504a1282ad14d2dee803adcf2019-11-05T21:18:27Z2019-11-05T21:18:27Z2019http://hdl.handle.net/11323/5578Corporación Universidad de la CostaREDICUC - Repositorio CUChttps://repositorio.cuc.edu.co/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.engUniversidad de la CostaCC0 1.0 Universalhttp://creativecommons.org/publicdomain/zero/1.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Artificial neural networkMultilayer perceptronDomestic violenceUse of Artificial Neural Networks in Determining Domestic Violence PredictorsPre-Publicaciónhttp://purl.org/coar/resource_type/c_816bTextinfo:eu-repo/semantics/preprinthttp://purl.org/redcol/resource_type/ARTOTRinfo:eu-repo/semantics/acceptedVersionORIGINALUse of Artificial Neural Networks in Determining Domestic Violence Predictors.pdfUse of Artificial Neural Networks in Determining Domestic Violence Predictors.pdfapplication/pdf73355https://repositorio.cuc.edu.co/bitstream/11323/5578/1/Use%20of%20Artificial%20Neural%20Networks%20in%20Determining%20Domestic%20Violence%20Predictors.pdff526d7dd6103278e077466cb4607a4beMD51open accessCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8701https://repositorio.cuc.edu.co/bitstream/11323/5578/2/license_rdf42fd4ad1e89814f5e4a476b409eb708cMD52open accessLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://repositorio.cuc.edu.co/bitstream/11323/5578/3/license.txt8a4605be74aa9ea9d79846c1fba20a33MD53open accessTHUMBNAILUse of Artificial Neural Networks in Determining Domestic Violence Predictors.pdf.jpgUse of Artificial Neural Networks in Determining Domestic Violence Predictors.pdf.jpgimage/jpeg38641https://repositorio.cuc.edu.co/bitstream/11323/5578/5/Use%20of%20Artificial%20Neural%20Networks%20in%20Determining%20Domestic%20Violence%20Predictors.pdf.jpg96b0e2c2c7ce7e1bac03b7a82b8c1d1dMD55open accessTEXTUse of Artificial Neural Networks in Determining Domestic Violence Predictors.pdf.txtUse of Artificial Neural Networks in Determining Domestic Violence Predictors.pdf.txttext/plain1230https://repositorio.cuc.edu.co/bitstream/11323/5578/6/Use%20of%20Artificial%20Neural%20Networks%20in%20Determining%20Domestic%20Violence%20Predictors.pdf.txt286e4033b527d39cb0c351823d79d85bMD56open access11323/5578oai:repositorio.cuc.edu.co:11323/55782023-12-14 12:07:58.498CC0 1.0 Universal|||http://creativecommons.org/publicdomain/zero/1.0/open accessRepositorio Universidad de La Costabdigital@metabiblioteca.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 |