%0 Journal Article
	%A Slimane Ouhmad and  Abdellah Halimi
	%D 2014
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 95, 2014
	%T The Impact of the Number of Neurons in the Hidden Layer on the Performance of MLP Neural Network: Application to the Fast Identification of Toxic Gases
	%U https://publications.waset.org/pdf/10000264
	%V 95
	%X In this work, neural networks methods MLP type were
applied to a database from an array of six sensors for the detection of
three toxic gases. The choice of the number of hidden layers and the
weight values are influential on the convergence of the learning
algorithm. We proposed, in this article, a mathematical formula to
determine the optimal number of hidden layers and good weight
values based on the method of back propagation of errors. The results
of this modeling have improved discrimination of these gases and
optimized the computation time. The model presented here has
proven to be an effective application for the fast identification of
toxic gases.

	%P 2060 - 2064