Comparison of neural networks and regression time series in estimating the Czech Republic and China trade balance
Foreign trade has been and is considered to be very important. Trade balance measurement provides one of the best analyzes of a country's external economic relations. It serves as a monetary expression of economic transactions between a certain country and its foreign partners over a certain pe...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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EDP Sciences
2019-01-01
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| Series: | SHS Web of Conferences |
| Subjects: | |
| Online Access: | https://www.shs-conferences.org/articles/shsconf/pdf/2019/02/shsconf_ies2018_01023.pdf |
| _version_ | 1818623722801594368 |
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| author | Rowland Zuzana Šuleř Petr Vochozka Marek |
| author_facet | Rowland Zuzana Šuleř Petr Vochozka Marek |
| author_sort | Rowland Zuzana |
| collection | DOAJ |
| description | Foreign trade has been and is considered to be very important. Trade balance measurement provides one of the best analyzes of a country's external economic relations. It serves as a monetary expression of economic transactions between a certain country and its foreign partners over a certain period. The aim of this paper is to compare the accuracy of time series alignment by means of regression analysis and neural networks on the example of the trade balance of the Czech Republic and the People's Republic of China. Trade balance data between the Czech Republic and the People's Republic of China is used. This is a monthly balance starting in 2000 and ending in July 2018. First, a linear regression is made followed by regression using artificial neural networks. A comparison of both methods at expert level and experience of the evaluator, the economist, is performed. Optically, the LOWESS curve appears to be best out of the linear regression and the fifth preserved RBF 1-24-1 network seems the mot appropriate out of neural networks. |
| first_indexed | 2024-12-16T18:45:35Z |
| format | Article |
| id | doaj.art-955f1dddabb7435bb75c6531e66d3e7d |
| institution | Directory Open Access Journal |
| issn | 2261-2424 |
| language | English |
| last_indexed | 2024-12-16T18:45:35Z |
| publishDate | 2019-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | SHS Web of Conferences |
| spelling | doaj.art-955f1dddabb7435bb75c6531e66d3e7d2022-12-21T22:20:51ZengEDP SciencesSHS Web of Conferences2261-24242019-01-01610102310.1051/shsconf/20196101023shsconf_ies2018_01023Comparison of neural networks and regression time series in estimating the Czech Republic and China trade balanceRowland ZuzanaŠuleř PetrVochozka MarekForeign trade has been and is considered to be very important. Trade balance measurement provides one of the best analyzes of a country's external economic relations. It serves as a monetary expression of economic transactions between a certain country and its foreign partners over a certain period. The aim of this paper is to compare the accuracy of time series alignment by means of regression analysis and neural networks on the example of the trade balance of the Czech Republic and the People's Republic of China. Trade balance data between the Czech Republic and the People's Republic of China is used. This is a monthly balance starting in 2000 and ending in July 2018. First, a linear regression is made followed by regression using artificial neural networks. A comparison of both methods at expert level and experience of the evaluator, the economist, is performed. Optically, the LOWESS curve appears to be best out of the linear regression and the fifth preserved RBF 1-24-1 network seems the mot appropriate out of neural networks.https://www.shs-conferences.org/articles/shsconf/pdf/2019/02/shsconf_ies2018_01023.pdfNeural networksRegression analysisComparisonTrade balancePrediction |
| spellingShingle | Rowland Zuzana Šuleř Petr Vochozka Marek Comparison of neural networks and regression time series in estimating the Czech Republic and China trade balance SHS Web of Conferences Neural networks Regression analysis Comparison Trade balance Prediction |
| title | Comparison of neural networks and regression time series in estimating the Czech Republic and China trade balance |
| title_full | Comparison of neural networks and regression time series in estimating the Czech Republic and China trade balance |
| title_fullStr | Comparison of neural networks and regression time series in estimating the Czech Republic and China trade balance |
| title_full_unstemmed | Comparison of neural networks and regression time series in estimating the Czech Republic and China trade balance |
| title_short | Comparison of neural networks and regression time series in estimating the Czech Republic and China trade balance |
| title_sort | comparison of neural networks and regression time series in estimating the czech republic and china trade balance |
| topic | Neural networks Regression analysis Comparison Trade balance Prediction |
| url | https://www.shs-conferences.org/articles/shsconf/pdf/2019/02/shsconf_ies2018_01023.pdf |
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