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Sistema Neurodifuso con Optimización por Enjambre de Partículas para la Clasificación de la Obesidad en Niños y Adolescentes
2016
Proceedings of the 14th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Engineering Innovations for Global Sustainability"
unpublished
The following article aims to classify obesity in children and male adolescents in a range from six to seventeen, using neural networks and fuzzy logic, for which the neuro-fuzzy model ANFIS (used artificial Neural Network Fuzzy Inference System) which is optimized using PSO (particle swarm optimization). Experimental tests show an error RMSE 8.31, after making 500 iterations of the algorithm PSO. This result is considered acceptable within the characteristics of this research conditions.
doi:10.18687/laccei2016.1.1.247
fatcat:464le2m3ljcihcbhp5kisxy6iu