Resumen
The objective of this article is to classify obesity in boys and adolescents, between 6 and 17 years old, using Neural Networks and Fuzzy Logic. The neuro-diffuse model ANFIS (Fuzzy Inference System of the Artificial Neural Network) was chosen, which is in the toolbox of Matlab. ANFIS includes a complete set of features for both the fuzzification, defuzzification, training and testing. Experimental tests show a 96.96% accuracy in classification and 3.04% error.
Título traducido de la contribución | Application of the ANFIS Neuro-Fuzzy model for the classification of obesity in children and adolescents |
---|---|
Idioma original | Español |
Título de la publicación alojada | Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology |
Editorial | Latin American and Caribbean Consortium of Engineering Institutions |
ISBN (versión digital) | 9780999344316 |
DOI | |
Estado | Publicada - 2018 |
Evento | 16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology - Lima, Perú Duración: 18 jul. 2018 → 20 jul. 2018 |
Serie de la publicación
Nombre | Proceedings of the LACCEI international Multi-conference for Engineering, Education and Technology |
---|---|
Volumen | 2018-July |
ISSN (versión digital) | 2414-6390 |
Conferencia
Conferencia | 16th LACCEI International Multi-Conference for Engineering, Education Caribbean Conference for Engineering and Technology |
---|---|
País/Territorio | Perú |
Ciudad | Lima |
Período | 18/07/18 → 20/07/18 |
Nota bibliográfica
Publisher Copyright:© 2018 Latin American and Caribbean Consortium of Engineering Institutions. All rights reserved.
Palabras clave
- ANFIS
- Accuracy
- BMI
- Classification
- Neuro-Fuzzy