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Using RBF neural networks to identify relationship between development of oil prices in world market and value of Chinese currency
- Source :
- SHS Web of Conferences, Vol 73, p 01008 (2020)
- Publication Year :
- 2020
- Publisher :
- EDP Sciences, 2020.
-
Abstract
- The objective of the contribution is to identify a possible relationship between the development of the price of Brent oil (Brent in USD/barrel) and the CNY / USD Exchange rate by means of artificial neural networks. Understanding future fluctuation characteristics and the trend in oil prices is the basis for a deep understanding of systemic mechanisms and trends in related research areas. However, given the complexities of oil prices, it is very difficult to obtain accurate forecasts. Within the experiment, a total of 50,000 artificial RBF neural networks were generated. Was found the CNY / USD price will play a significant role in creating China's real product. Given that it was already proven that the CNY / USD exchange depends on Brent in USD / barrel, it is important to focus the further research on finding out the time lag with which the price of Brent in USD / barrel is actually reflected in the price of CNY / USD.
- Subjects :
- rbf neural networks
value
oil prices
exchange rate
Social Sciences
Subjects
Details
- Language :
- English, French
- ISSN :
- 22612424 and 20207301
- Volume :
- 73
- Database :
- Directory of Open Access Journals
- Journal :
- SHS Web of Conferences
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.9b58c693f832465b9f2dc2cfa0b64333
- Document Type :
- article
- Full Text :
- https://doi.org/10.1051/shsconf/20207301008