Proceedings of the International Scientific-Practical Conference “Business Cooperation as a Resource of Sustainable Economic Development and Investment Attraction” (ISPCBC 2019)

Spatial-temporal digital twin models as a direction for the development of cross-cutting digital technologies

Authors
G. Malykhina, A. Guseva, A. Militsyn
Corresponding Author
G. Malykhina
Available Online August 2019.
DOI
https://doi.org/10.2991/ispcbc-19.2019.18How to use a DOI?
Keywords
digital twin; neural network solution; machine learning; fire system
Abstract

The proposed spatial-time digital twin model is based on a neural network approach for solving partial differential equations characterizing a physical object. The model aims to develop cross-cutting digital technologies. This approach makes it possible to account newly received data and thereby maintain the relevance of the model. The approach allows integrating the knowledge of specialists and engineers for solving a number of important tasks. The model uses machine learning and is therefore adaptive.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Cite this article

TY  - CONF
AU  - G. Malykhina
AU  - A. Guseva
AU  - A. Militsyn
PY  - 2019/08
DA  - 2019/08
TI  - Spatial-temporal digital twin models as a direction for the development of cross-cutting digital technologies
BT  - Proceedings of the International Scientific-Practical Conference “Business Cooperation as a Resource of Sustainable Economic Development and Investment Attraction” (ISPCBC 2019)
PB  - Atlantis Press
SP  - 569
EP  - 572
SN  - 2352-5428
UR  - https://doi.org/10.2991/ispcbc-19.2019.18
DO  - https://doi.org/10.2991/ispcbc-19.2019.18
ID  - Malykhina2019/08
ER  -