Mathematical Simulation of Dynamics on the Basis of Analysis of Multidimensional Time Series with Consideration for Lagged Influence of Factors Using Neural Networks
Oleg Yakovlevich Kravets1, Evgeny Efimovich Krasnovskiy2, Irina Nikolaevna Kryuchkova3, Evgeniya Vitalievna Bolnokina4, Vladimir Dmitriyevich Sekerin5

1Evgeny Efimovich Krasnovskiy, Bauman Moscow State Technical University, Baumanskaya 2-ya St., 5/1, Moscow, 105005, Russia.
2Irina Nikolaevna Kryuchkova, Voronezh State Technical University, 20 years of October St., 84, Voronezh, 394006, Russia.
3Evgeniya Vitalievna Bolnokina, Voronezh State Technical University, 20 years of October St., 84, Voronezh, 394006, Russia.
4Vladimir Dmitriyevich Sekerin, Kuban State Agrarian University, Kalinina Str., 13, Krasnodar, 350044, Russia
5V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences, Profsoyuznaya St., 65, Moscow, 117997, Russia.

Manuscript received on 18 February 2019 | Revised Manuscript received on 27 February 2019 | Manuscript published on 28 February 2019 | PP: 163-167 | Volume-8 Issue-3, February 2019 | Retrieval Number: C587702831919/19©BEIESP
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Abstract: This article investigates into the models and methods of neural simulation of dynamics on the basis of analysis of multidimensional time series with consideration for lagged influence of significant factors. Mathematical formulation of the neural network construction for nonzero lag is presented, peculiarities of lag optimization are described for one independent variable (input), simulation and forecast database is specified as well as neural algorithms of data processing, algorithmization of multivariate regression analysis is carried out with optimization of lag vector for significant factors.
Keywords: Mathematical Simulation, Neural Networks, lag.

Scope of the Article: Cryptography and Applied Mathematics