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of 4
pro vyhledávání: '"Guangxun Jin"'
Impact of chart image characteristics on stock price prediction with a convolutional neural network.
Autor:
Guangxun Jin, Ohbyung Kwon
Publikováno v:
PLoS ONE, Vol 16, Iss 6, p e0253121 (2021)
Stock price prediction has long been the subject of research because of the importance of accuracy of prediction and the difficulty in forecasting. Traditionally, forecasting has involved linear models such as AR and MR or nonlinear models such as AN
Externí odkaz:
https://doaj.org/article/16261ef392e24660be94f1a554572d09
Autor:
Ohbyung Kwon, Guangxun Jin
Publikováno v:
PLoS ONE
PLoS ONE, Vol 16, Iss 6, p e0253121 (2021)
PLoS ONE, Vol 16, Iss 6, p e0253121 (2021)
Stock price prediction has long been the subject of research because of the importance of accuracy of prediction and the difficulty in forecasting. Traditionally, forecasting has involved linear models such as AR and MR or nonlinear models such as AN
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f02b0a96156e1f3770d13035f796413c
https://pubmed.ncbi.nlm.nih.gov/34161352
https://pubmed.ncbi.nlm.nih.gov/34161352
Publikováno v:
The Journal of the Korea Contents Association. 10:45-56
This paper reports a new mechanism for congestion controls. The proposed congestion detection algorithm can be provided with delay and unnecessary energy consumption. Conventional congestion control methods decide congestion by queue occupancy or mea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::72fba2fbca30a4224bdd06bd3299508f
https://doi.org/10.5392/jkca.2010.10.9.045
https://doi.org/10.5392/jkca.2010.10.9.045