APPLICATION OF MACHINE LEARNING IN THE MODELING OF PHYSICAL PROCESSES

Authors

  • Valentyn Kuzmych National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine
  • Mykhailo Novotarskyi National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, Ukraine

Keywords:

modeling, artificial neural networks, lattice Boltzmann model, machine learning, computational fluid dynamics

Abstract

The article gives an overview of modern approaches to the application of machine learning in the modeling of physical processes on the example of fluid motion in space. The structure and capabilities of artificial neural networks in the modeling of complex physical processes are described.

References

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Guo, Xiaoxiao & Li, Wei & Iorio, Francesco (2016). Convolutional Neural Networks for Steady Flow Approximation [Електронний ресурс] //ResearchGate URL: https://www.researchgate.net/publication/305997840_Convolutional_Neural_Networks_for_Steady_Flow_Approximation (дата звернення: 25.04.2020).

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Published

2023-06-08

Issue

Section

Machine learning, Big Data