Comparison of neural networks and regression time series when
predicting the export development from the USA to PRC

D 2019

Comparison of neural networks and regression time series when predicting the export development from the USA to PRC

HORÁK, Jakub, Petr ŠULEŘ a Jaromír VRBKA

Základní údaje

Originální název

Comparison of neural networks and regression time series when predicting the export development from the USA to PRC

Autoři

HORÁK, Jakub (203 Česká republika, garant, domácí), Petr ŠULEŘ (203 Česká republika, domácí) a Jaromír VRBKA (203 Česká republika, domácí)

Vydání

Vilnius, Litva, International Scientific Conference Contemporary Issues In Business, Management and Economics Engineering’2019, od s. 170-180, 899 s. 2019

Nakladatel

Vilnius Gediminas Technical University

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

50200 5.2 Economics and Business

Stát vydavatele

Litva

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Odkazy

URL

Kód RIV

RIV/75081431:_____/19:00002430

Organizační jednotka

Vysoká škola technická a ekonomická v Českých Budějovicích

ISBN

978-609-476-162-1

Klíčová slova anglicky

Artificial neural networks; regression analysis; time series; export; prediction

Štítky

NE_MAE, RIV22

Změněno: 4. 11. 2022 07:51, Mgr. Nikola Petříková

Anotace

V originále

The authors aim is to examine the relationship between interest rates of ten-year government bonds and selected macroeconomic indicators. In order to meet the objective of this contribution, the following is used: gross domestic product, inflation and unemployment. Regression using artificial neural networks is used as the basic method.

Přiložené soubory

Comparison_of_neural_networks_and_regression_time_series_when_predicting_the_export_de.pdf

Požádat o autorskou verzi souboru

Citovat

HORÁK, Jakub, Petr ŠULEŘ a Jaromír VRBKA. Comparison of neural networks and regression time series when predicting the export development from the USA to PRC. Online. In Viktorija Skvarciany, Jelena Stankeviciene, Raimonda Martinkute-Kauliene, Izolda Joksiene, Alma Maciulyte-Sniukiene, Andrius Tamosiunas, Sigitas Mitkus, Daiva Jureviciene, Algita Miecinskiene, Ilona Skackauskiene, Vida Davidaviciene. International Scientific Conference Contemporary Issues In Business, Management and Economics Engineering’2019. Vilnius, Litva: Vilnius Gediminas Technical University, 2019, s. 170-180, 899 s. ISBN 978-609-476-162-1.

@inproceedings{65041,
   author = {Horák, Jakub and Šuleř, Petr and Vrbka, Jaromír},
   address = {Vilnius, Litva},
   booktitle = {International Scientific Conference Contemporary Issues In Business, Management and Economics Engineering’2019},
   editor = {Viktorija Skvarciany, Jelena Stankeviciene, Raimonda Martinkute-Kauliene, Izolda Joksiene, Alma Maciulyte-Sniukiene, Andrius Tamosiunas, Sigitas Mitkus, Daiva Jureviciene, Algita Miecinskiene, Ilona Skackauskiene, Vida Davidaviciene},
   keywords = {Artificial neural networks; regression analysis; time series; export; prediction},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Vilnius, Litva},
   isbn = {978-609-476-162-1},
   pages = {170-180},
   publisher = {Vilnius Gediminas Technical University},
   title = {Comparison of neural networks and regression time series when predicting the export development from the USA to PRC},
   url = {http://cibmee.vgtu.lt/index.php/verslas/2019/paper/view/428},
   year = {2019}
}

TY  - JOUR
ID  - 65041
AU  - Horák, Jakub - Šuleř, Petr - Vrbka, Jaromír
PY  - 2019
TI  - Comparison of neural networks and regression time series when predicting the export development from the USA to PRC
PB  - Vilnius Gediminas Technical University
CY  - Vilnius, Litva
SN  - 9786094761621
KW  - Artificial neural networks
KW  - regression analysis
KW  - time series
KW  - export
KW  - prediction
UR  - http://cibmee.vgtu.lt/index.php/verslas/2019/paper/view/428
N2  - The authors aim is to examine the relationship between interest rates of ten-year government bonds and selected macroeconomic indicators. In order to meet the objective of this contribution, the following is used: gross domestic product, inflation and unemployment. Regression using artificial neural networks is used as the basic method.
ER  -

HORÁK, Jakub, Petr ŠULEŘ a Jaromír VRBKA. Comparison of neural networks and regression time series when predicting the export development from the USA to PRC. Online. In Viktorija Skvarciany, Jelena Stankeviciene, Raimonda Martinkute-Kauliene, Izolda Joksiene, Alma Maciulyte-Sniukiene, Andrius Tamosiunas, Sigitas Mitkus, Daiva Jureviciene, Algita Miecinskiene, Ilona Skackauskiene, Vida Davidaviciene. \textit{International Scientific Conference Contemporary Issues In Business, Management and Economics Engineering’2019}. Vilnius, Litva: Vilnius Gediminas Technical University, 2019, s.~170-180, 899 s. ISBN~978-609-476-162-1.

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