519.237.07 Factorial modeling using neural network

Chauvigny V. A. (Sobolev Institute of Mathematics, Omsk branch, Siberian Branch of the Russian Academy of Sciences), Goltiapin V. V. (Sobolev Institute of Mathematics, Omsk branch, Siberian Branch of the Russian Academy of Sciences)

ARTERIAL HYPERTENSION, FACTOR ANALYSIS, NEURAL NETWORKS, BACK PROPAGATION OF ERROR


doi: 10.18698/2309-3684-2016-2-85103


The paper deals with the factorial modeling of the initial stage arterial hypertension. The modeling was carried out by the factorization method based on the neural network and the back propagation of error algorithm. This factorization method is an alternative to the classical factor analysis. We implemented an algorithm for constructing the factorial structure based on the neural network in software. This method has been improved for the factor rotation and obtaining an interpretable solution. The hypertension factorial structure obtained by this factorization method is in accordance with the results of the factorial modeling by other methods.


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Chauvigny V., Goltiapin V. Factorial modeling using neural network. Маthematical Modeling and Coтputational Methods, 2016, №2 (10), pp. 85-103



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