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Agricultural Economic Risk Forecast Based on Data Mining Technology
In order to improve the effect of agricultural economic risk forecast, this paper studies the agricultural economic risk forecast combined with data mining technology and builds an intelligent agricultural economic risk forecast system. Moreover, this paper employs a dynamic factor model to estimate...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9068313/ https://www.ncbi.nlm.nih.gov/pubmed/35528359 http://dx.doi.org/10.1155/2022/3684736 |
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author | Wang, Lei Tan, Hongwei |
author_facet | Wang, Lei Tan, Hongwei |
author_sort | Wang, Lei |
collection | PubMed |
description | In order to improve the effect of agricultural economic risk forecast, this paper studies the agricultural economic risk forecast combined with data mining technology and builds an intelligent agricultural economic risk forecast system. Moreover, this paper employs a dynamic factor model to estimate common factors that drive changes in target topics. In order to construct a sentiment index that can reflect the overall operating situation of the macroeconomy, this paper improves the agricultural economic risk mining algorithm and standardizes the sentiment value corresponding to the target theme. In addition, this article analyzes the sentiment changes of its individual topics one by one in combination with the specific economic environment. The simulation study shows that the agricultural economic risk forecast system based on data mining technology proposed in this paper has a good effect. |
format | Online Article Text |
id | pubmed-9068313 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-90683132022-05-05 Agricultural Economic Risk Forecast Based on Data Mining Technology Wang, Lei Tan, Hongwei Comput Intell Neurosci Research Article In order to improve the effect of agricultural economic risk forecast, this paper studies the agricultural economic risk forecast combined with data mining technology and builds an intelligent agricultural economic risk forecast system. Moreover, this paper employs a dynamic factor model to estimate common factors that drive changes in target topics. In order to construct a sentiment index that can reflect the overall operating situation of the macroeconomy, this paper improves the agricultural economic risk mining algorithm and standardizes the sentiment value corresponding to the target theme. In addition, this article analyzes the sentiment changes of its individual topics one by one in combination with the specific economic environment. The simulation study shows that the agricultural economic risk forecast system based on data mining technology proposed in this paper has a good effect. Hindawi 2022-04-27 /pmc/articles/PMC9068313/ /pubmed/35528359 http://dx.doi.org/10.1155/2022/3684736 Text en Copyright © 2022 Lei Wang and Hongwei Tan. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Wang, Lei Tan, Hongwei Agricultural Economic Risk Forecast Based on Data Mining Technology |
title | Agricultural Economic Risk Forecast Based on Data Mining Technology |
title_full | Agricultural Economic Risk Forecast Based on Data Mining Technology |
title_fullStr | Agricultural Economic Risk Forecast Based on Data Mining Technology |
title_full_unstemmed | Agricultural Economic Risk Forecast Based on Data Mining Technology |
title_short | Agricultural Economic Risk Forecast Based on Data Mining Technology |
title_sort | agricultural economic risk forecast based on data mining technology |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9068313/ https://www.ncbi.nlm.nih.gov/pubmed/35528359 http://dx.doi.org/10.1155/2022/3684736 |
work_keys_str_mv | AT wanglei agriculturaleconomicriskforecastbasedondataminingtechnology AT tanhongwei agriculturaleconomicriskforecastbasedondataminingtechnology |