Lyudmila O. Tereykovska

Work place: Kyiv National University of Construction and Architecture, Kyiv, Ukraine



Research Interests: Computer systems and computational processes, Neural Networks, Pattern Recognition, Network Architecture, Speech Recognition, Data Mining, Analysis of Algorithms, Theory of Computation, Models of Computation


Lyudmila O. Tereykovska graduated from State Academy of Light Industry of Ukraine, Kiev. Currently, she is a PhD, associate professor at Kyiv National University of Construction and Architecture, Ukraine. She has currently published more than 20 publications.

Her research interests are data mining, development of neural network systems, recognition of voice signals, the construction of distance education systems, recognition of cyber-attacks.

Author Articles
Determination of Structural Parameters of Multilayer Perceptron Designed to Estimate Parameters of Technical Systems

By Zhengbing Hu Igor A. Tereykovskiy Lyudmila O. Tereykovska Volodymyr V. Pogorelov

DOI:, Pub. Date: 8 Oct. 2017

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.

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