Intelligent Informatization Early Warning Analysis of Agricultural Economy Based on Support Vector Sequential Regression Model
The development of science and technology has laid a solid foundation for the economic informatization of agriculture, and at the same time it brought technical guarantee for the development of agriculture, and the development of agriculture has provided an important material foundation for the deve...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2021/6334444 |
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| _version_ | 1832546018722316288 |
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| author | Ying Yang |
| author_facet | Ying Yang |
| author_sort | Ying Yang |
| collection | DOAJ |
| description | The development of science and technology has laid a solid foundation for the economic informatization of agriculture, and at the same time it brought technical guarantee for the development of agriculture, and the development of agriculture has provided an important material foundation for the development of science and technology. How to identify and deeply study agricultural economic informatization, give early warning to risk information, and ensure the steady development of the whole industry has become a key issue in the application of Internet technology in the field of agricultural development. This paper studies the present situation of agricultural economy informatization development process and applies support vector machine to forecast regional economic development level. The warning limit of agricultural economic growth rate is obtained on the basis of warning situation and warning indicator in early warning index system. The economic early warning model is established based on the support vector sequential regression method, and then the data is trained by MATLAB software to verify the rationality of the early warning model, and the accuracy and corresponding error of the model are given. Experimental results show that the prediction accuracy is 99.3%, the error is less than 0.05, and the prediction effect is relatively ideal, for agricultural economic intelligence information to provide accurate warning and agricultural economic research agricultural commercial development to provide support. |
| format | Article |
| id | doaj-art-cd78b5ffa0e74e4799cb22223956ac0d |
| institution | Kabale University |
| issn | 2314-4785 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-cd78b5ffa0e74e4799cb22223956ac0d2025-02-03T07:24:11ZengWileyJournal of Mathematics2314-47852021-01-01202110.1155/2021/6334444Intelligent Informatization Early Warning Analysis of Agricultural Economy Based on Support Vector Sequential Regression ModelYing Yang0School of Business AdministrationThe development of science and technology has laid a solid foundation for the economic informatization of agriculture, and at the same time it brought technical guarantee for the development of agriculture, and the development of agriculture has provided an important material foundation for the development of science and technology. How to identify and deeply study agricultural economic informatization, give early warning to risk information, and ensure the steady development of the whole industry has become a key issue in the application of Internet technology in the field of agricultural development. This paper studies the present situation of agricultural economy informatization development process and applies support vector machine to forecast regional economic development level. The warning limit of agricultural economic growth rate is obtained on the basis of warning situation and warning indicator in early warning index system. The economic early warning model is established based on the support vector sequential regression method, and then the data is trained by MATLAB software to verify the rationality of the early warning model, and the accuracy and corresponding error of the model are given. Experimental results show that the prediction accuracy is 99.3%, the error is less than 0.05, and the prediction effect is relatively ideal, for agricultural economic intelligence information to provide accurate warning and agricultural economic research agricultural commercial development to provide support.http://dx.doi.org/10.1155/2021/6334444 |
| spellingShingle | Ying Yang Intelligent Informatization Early Warning Analysis of Agricultural Economy Based on Support Vector Sequential Regression Model Journal of Mathematics |
| title | Intelligent Informatization Early Warning Analysis of Agricultural Economy Based on Support Vector Sequential Regression Model |
| title_full | Intelligent Informatization Early Warning Analysis of Agricultural Economy Based on Support Vector Sequential Regression Model |
| title_fullStr | Intelligent Informatization Early Warning Analysis of Agricultural Economy Based on Support Vector Sequential Regression Model |
| title_full_unstemmed | Intelligent Informatization Early Warning Analysis of Agricultural Economy Based on Support Vector Sequential Regression Model |
| title_short | Intelligent Informatization Early Warning Analysis of Agricultural Economy Based on Support Vector Sequential Regression Model |
| title_sort | intelligent informatization early warning analysis of agricultural economy based on support vector sequential regression model |
| url | http://dx.doi.org/10.1155/2021/6334444 |
| work_keys_str_mv | AT yingyang intelligentinformatizationearlywarninganalysisofagriculturaleconomybasedonsupportvectorsequentialregressionmodel |