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  • 标题:Using RBF neural networks to identify relationship between development of oil prices in world market and value of Chinese currency
  • 本地全文:下载
  • 作者:akub Horák ; Jaromír Vrbka ; Tomáš Krulický
  • 期刊名称:SHS Web of Conferences
  • 印刷版ISSN:2416-5182
  • 电子版ISSN:2261-2424
  • 出版年度:2020
  • 卷号:73
  • 页码:1-12
  • DOI:10.1051/shsconf/20207301008
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要: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.
  • 关键词:RBF neural networks;value;oil prices;exchange rate
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