2016
DOI: 10.14569/ijarai.2016.051204
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Neural Backpropagation System for the Study of Obesity in Childhood

Abstract: Abstract-This paper presents the development of a nutritional system using Backpropagation neural network, that is able to provide a clear and simple prediction problems of obesity in children up to twelve years, based on your eating habits during the day. For the development of this project has taken into account various factors, which are vital for the proper development of infants. A prediction system can offer a solution to several factors, which are not easily determined by convectional means.

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Cited by 2 publications
(1 citation statement)
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“…In [1], the complexity of the human brain is amazing, consisting of hundreds of billions of neurons with billions of connections that make the neural function of the brain very complex. In [2], the artificial neural networks are systems that simulate the properties that are observed in the biological diversity through mathematical models that are recreated by artificial mechanisms. Artificial neural networks are information processing systems that are inspired by the behavior of biological neural networks [3], [4], [5].…”
Section: Introductionmentioning
confidence: 99%
“…In [1], the complexity of the human brain is amazing, consisting of hundreds of billions of neurons with billions of connections that make the neural function of the brain very complex. In [2], the artificial neural networks are systems that simulate the properties that are observed in the biological diversity through mathematical models that are recreated by artificial mechanisms. Artificial neural networks are information processing systems that are inspired by the behavior of biological neural networks [3], [4], [5].…”
Section: Introductionmentioning
confidence: 99%