Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Zian Dai"'
Publikováno v:
Tehnički Vjesnik, Vol 30, Iss 2, Pp 499-505 (2023)
In the financial markets, the heterogeneity of investors is mostly focusing on very different underlying assets. However, there is one specific heterogeneity need to be discussed, that is the heterogeneity represented by investors who are investing i
Externí odkaz:
https://doaj.org/article/b9dfaa8bb1a241e3933b29a4476498cd
Publikováno v:
Tehnički Vjesnik, Vol 26, Iss 4, Pp 1098-1103 (2019)
In this study, we aim to estimate the density distribution for the return intervals of extreme temperature fluctuation in blast furnace during iron making process. We first identified the fractal feature of the data based on R/S analysis and also cal
Externí odkaz:
https://doaj.org/article/4bc906b1f3764d25904a84a12a3ebfe2
Frequency-Division Combination Forecasting of Stock Market Based on Wavelet Multiresolution Analysis
Publikováno v:
Discrete Dynamics in Nature and Society, Vol 2018 (2018)
Put forward a novel combination forecasting method (M-ARIMA-BP) that could make a more accurate and concise prediction of stock market based on wavelet multiresolution analysis. This innovative method operated by parsing of the low-frequency trend se
Externí odkaz:
https://doaj.org/article/7318e0ed85fd488b86262d207021815d
Publikováno v:
Applied Intelligence. 50:1997-2008
As one of the most complex industrial reactors, there remain some urgent issues for blast furnace (BF), such as BF automation, prediction of the inner thermal state, etc. In this work, the prediction of BF inner thermal state, which is represented by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be3cca0e0123ff6592a5913a5ed67353
https://doi.org/10.1007/s10489-020-01662-y
https://doi.org/10.1007/s10489-020-01662-y
Frequency-Division Combination Forecasting of Stock Market Based on Wavelet Multiresolution Analysis
Publikováno v:
Discrete Dynamics in Nature and Society, Vol 2018 (2018)
Put forward a novel combination forecasting method (M-ARIMA-BP) that could make a more accurate and concise prediction of stock market based on wavelet multiresolution analysis. This innovative method operated by parsing of the low-frequency trend se
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2284fdd7f7e87ac880899917d721c65b
https://doi.org/10.1155/2018/1259156
https://doi.org/10.1155/2018/1259156
Publikováno v:
Tehnički vjesnik
Volume 26
Issue 4
Tehnički Vjesnik, Vol 26, Iss 4, Pp 1098-1103 (2019)
Volume 26
Issue 4
Tehnički Vjesnik, Vol 26, Iss 4, Pp 1098-1103 (2019)
In this study, we aim to estimate the density distribution for the return intervals of extreme temperature fluctuation in blast furnace during iron making process. We first identified the fractal feature of the data based on R/S analysis and also cal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1c4f789fcca8f1c2e806b4e168e78ad7
https://hrcak.srce.hr/file/325834
https://hrcak.srce.hr/file/325834