How to use neural network and web technologies in modeling complex technical systems
М. Г. СемененкоRANEPA, Kaluga branch, 4, Okruzhnaya street, Kaluga, 248016, RussiaI V KniazevaFinancial University under the Government of the Russian Federation, Kaluga branch, 17, Chizhevsky street, Kaluga, 248016, RussiaL S BeckelBauman Moscow State Technical University, Kaluga branch, 2, Bazhenova street, Kaluga, 248000, RussiaVladislav RutskiySiberian Federal University, 79, Svobodny pr., Krasnoyarsk, 660041, RussiaRoman TsarevSiberian Federal University, 79, Svobodny pr., Krasnoyarsk, 660041, RussiaT N YamskikhSiberian Federal University, 79, Svobodny pr., Krasnoyarsk, 660041, RussiaIgor KartsanReshetnev Siberian State University of Science and Technology, 31, Krasnoyarsky Rabochy Ave., Krasnoyarsk, 660037, Russia
2019en
ABI
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Abstract This paper discusses the problem of integrating modern methods of forecasting and modeling complex technical objects into the learning process. As an example, the problem of solving a system of ordinary differential equations is considered, which has significant practical application. In particular, solving a system of differential equations can be an essential part of patents. The neural network method to solve this problem by using Matlab simulation software and visual modeling tool Simulink is considered. Efficient cloud-based solution to ordinary differential equations is presented.
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