Self-learning systems as a new macro-regional level of the productive forces in the process of new industrialization
- https://doi.org/10.2991/sicni-18.2019.173How to use a DOI?
- new industrialization, region development, the fourth industrial revolution, Urals macro-region, the system of decision-making support.
The concepts of new industrialization based on the evolutionary model of the fourth industrial revolution are studied in the article, the term “new industrialization” is clarified, the innovative activity of Russian regions is analyzed, thus, based on the aspects above, the directions of structural reforms that will ensure the activation of new industrialization processes formation in the economic space of the Urals macro-region are highlighted. For this reason the authors consider the main development vectors formation of the new industrial sector to proceed according to the regional requirements of life standards. It involves the application of system approach principle, basing on the new industrialization concept as a social and economic category. It is also proved that enterprises should actively implement self-learning management systems based on artificial intellect, thereby increasing both financial and reputational management efficiency. An example of self-learning systems scheme that can dynamically manage their internal processes basing on a flexible assessment of their effectiveness is illustrated.
- © 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/).
Cite this article
TY - CONF AU - Anna Tikhonova AU - Natalya Sosnina AU - Dina Prostova PY - 2019/01 DA - 2019/01 TI - Self-learning systems as a new macro-regional level of the productive forces in the process of new industrialization BT - Proceedings of the 2nd International Scientific conference on New Industrialization: Global, national, regional dimension (SICNI 2018) PB - Atlantis Press SP - 860 EP - 865 SN - 2352-5398 UR - https://doi.org/10.2991/sicni-18.2019.173 DO - https://doi.org/10.2991/sicni-18.2019.173 ID - Tikhonova2019/01 ER -