Application of Neural Networks to Studying the Impact of the Russian Central Bank’s Monetary Policy

DOI

10.2991/iscfec-18.2019.281How to use a DOI?

Keywords

perceptron, neural-network algorithm, digital economy, perceptron, the CBR rate, prediction.

Abstract

The paper presents analysis of the Russian Federation’s monetary policy. The Central Bank’s key rate is an important parameter. It is hypothesized that the key rate (KR) could be predicted by means of artificial intelligence, a perceptron, the input of which is generated by neural-network quantization. Applying the results of such “smart” analysis to predicting the CBR key rate seems appropriate.

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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TY  - CONF
AU  - N. I. Lomakin
AU  - O.A. Golodova
AU  - O. M. Burdyugova
PY  - 2019/01
DA  - 2019/01
TI  - Application of Neural Networks to Studying the Impact of the Russian Central Bank’s Monetary Policy
BT  - Proceedings of the International Scientific Conference "Far East Con" (ISCFEC 2018)
PB  - Atlantis Press
SP  - 1245
EP  - 1248
SN  - 2352-5428
UR  - https://doi.org/10.2991/iscfec-18.2019.281
DO  - 10.2991/iscfec-18.2019.281
ID  - Lomakin2019/01
ER  -