Determination of structural parameters of multilayer perceptron designed to estimate parameters of technical systems
Автор: Zhengbing Hu, Igor A. Tereykovskiy, Lyudmila O. Tereykovska, Volodymyr V. Pogorelov
Журнал: International Journal of Intelligent Systems and Applications @ijisa
Статья в выпуске: 10 vol.9, 2017 года.
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The paper is dedicated to the problem of efficiency increasing in case of applying multilayer perceptron in context of parameters estimation for technical systems. It is shown that the increase of efficiency is possible by adaptation of structure of the multilayer perceptron to the problem specification set. It is revealed that the structure adaptation lies in the determination the following parameters: 1. The number of hidden neuron layers; 2. The number of neurons within each layer. In terms of the paper, we introduce mathematical apparatus that allows conducting the structure adaptation for minimization of the relative error of the neuro-network model generalization. A numerical experiment to demonstrate efficiency of the mathematical apparatus was developed and described in terms of the article. Further research in this sphere lies in the development of a method for calculation of optimum relationship between the number of the hidden neuron layers and the number of hidden neurons within each layer.
Neuro-network model generalization, Structure of multilayer perceptron, Hidden neuron layer, Hidden neuron, Structure adaptation
Короткий адрес: https://sciup.org/15016427
IDR: 15016427 | DOI: 10.5815/ijisa.2017.10.07
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