Application of the BP Neural Network Model of Gray Relational Analysis in Economic Management
According to the BP neural network algorithm, for the problem that the input variables of the BP network cannot be automatically optimized during the modeling process of the multivariable complex system, it is used to establish a neural network optimization algorithm according to the gray correlatio...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2022/4359383 |
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| author | Zhuojie Li |
| author_facet | Zhuojie Li |
| author_sort | Zhuojie Li |
| collection | DOAJ |
| description | According to the BP neural network algorithm, for the problem that the input variables of the BP network cannot be automatically optimized during the modeling process of the multivariable complex system, it is used to establish a neural network optimization algorithm according to the gray correlation analysis (GM2 BPANN). Using the data of China’s grain production forecast, the stepwise regression method and the gray GM (1, N) model method were compared and tested. The results show that the new model can comprehensively and extensively process a large number of input variables by using the concept of the gray correlation degree, without having to go through special subjective screening and hence improving the adaptability of the BP network, and at the same time, it can obtain better prediction accuracy and stability. Through the empirical test, the prediction ability of the three methods of regression, GM (1, N) gray system, and GM-BPANN model is compared. It is proved that the GM-BPANN optimization algorithm that combines the gray relational analysis and BP neural network method can enhance the multivariable processing ability and network adaptability of the BP network and has good prediction accuracy and stability. |
| format | Article |
| id | doaj-art-ea7a815b9d3f4b52919081833771d186 |
| institution | Kabale University |
| issn | 2314-4785 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-ea7a815b9d3f4b52919081833771d1862025-02-03T00:59:32ZengWileyJournal of Mathematics2314-47852022-01-01202210.1155/2022/4359383Application of the BP Neural Network Model of Gray Relational Analysis in Economic ManagementZhuojie Li0Department of Economics and ManagementAccording to the BP neural network algorithm, for the problem that the input variables of the BP network cannot be automatically optimized during the modeling process of the multivariable complex system, it is used to establish a neural network optimization algorithm according to the gray correlation analysis (GM2 BPANN). Using the data of China’s grain production forecast, the stepwise regression method and the gray GM (1, N) model method were compared and tested. The results show that the new model can comprehensively and extensively process a large number of input variables by using the concept of the gray correlation degree, without having to go through special subjective screening and hence improving the adaptability of the BP network, and at the same time, it can obtain better prediction accuracy and stability. Through the empirical test, the prediction ability of the three methods of regression, GM (1, N) gray system, and GM-BPANN model is compared. It is proved that the GM-BPANN optimization algorithm that combines the gray relational analysis and BP neural network method can enhance the multivariable processing ability and network adaptability of the BP network and has good prediction accuracy and stability.http://dx.doi.org/10.1155/2022/4359383 |
| spellingShingle | Zhuojie Li Application of the BP Neural Network Model of Gray Relational Analysis in Economic Management Journal of Mathematics |
| title | Application of the BP Neural Network Model of Gray Relational Analysis in Economic Management |
| title_full | Application of the BP Neural Network Model of Gray Relational Analysis in Economic Management |
| title_fullStr | Application of the BP Neural Network Model of Gray Relational Analysis in Economic Management |
| title_full_unstemmed | Application of the BP Neural Network Model of Gray Relational Analysis in Economic Management |
| title_short | Application of the BP Neural Network Model of Gray Relational Analysis in Economic Management |
| title_sort | application of the bp neural network model of gray relational analysis in economic management |
| url | http://dx.doi.org/10.1155/2022/4359383 |
| work_keys_str_mv | AT zhuojieli applicationofthebpneuralnetworkmodelofgrayrelationalanalysisineconomicmanagement |