Performance Analysis with Artificial Neural Networks, MLP and RBF Architectures for a Problem of Classification of Children with Autism


  • Rhyan Ximenes de Brito IFCE - Instituto Federal de Educação, Ciência e Tecnologia do Ceará
  • Carlos Alexandre Rolim Fernandes Universidade Federal do Ceará



Artificial Neural Networks has been outstanding in solving problems in several areas. In this sense, a study was carried out with the implementation and analysis of the Multilayer Perceptron (MLP) and Radial Basis Function Neural Network (RBF) networks, in order to compare results based on training, test and classification of children with or without autism. The methodology was implemented based on 292 samples of individuals from a public database, using the Matlab tool R2015a, divided into 10 parts with cross validation. The results were analyzed considering the different characteristics and behaviors of the implemented networks, obtaining a measure of the quality reached.


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How to Cite

de Brito, R. X., & Fernandes, C. A. R. (2021). Performance Analysis with Artificial Neural Networks, MLP and RBF Architectures for a Problem of Classification of Children with Autism. ISys - Brazilian Journal of Information Systems, 13(1).



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