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Deep Intelligence-Driven Efficient Forecasting for the Agriculture Economy of Computational Social Systems
In the vision of smart cities, everything is highly connected with the aid of computational intelligence. Therefore, the cyber-physical society has been named a computational social system for a long time. Due to the high relation with vast populations' national livelihood, agriculture will sti...
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/PMC9532071/ https://www.ncbi.nlm.nih.gov/pubmed/36203731 http://dx.doi.org/10.1155/2022/2854675 |
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author | Li, Xuelan Li, Xiao Jiang, Jiyu |
author_facet | Li, Xuelan Li, Xiao Jiang, Jiyu |
author_sort | Li, Xuelan |
collection | PubMed |
description | In the vision of smart cities, everything is highly connected with the aid of computational intelligence. Therefore, the cyber-physical society has been named a computational social system for a long time. Due to the high relation with vast populations' national livelihood, agriculture will still serve as a core industry in the national economy. As a result, this study focused on an efficient forecasting method for the agriculture economy. In recent years, the conception of deep intelligence has received overall prevalence in academia because of its excellent performance in implementing intelligent information processing tasks. Hence, this paper utilized deep intelligence driven by neural networks and managed to investigate an efficient prediction method for the agriculture economy of computational social systems. To fit the time-series forecasting scene of the long-term development of the agriculture economy, the convolutional neural network model is slightly improved by revising its parallel structure into the recurrent format. Finally, simulations on realistic datasets are carried out to evaluate the proposed forecasting method. |
format | Online Article Text |
id | pubmed-9532071 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-95320712022-10-05 Deep Intelligence-Driven Efficient Forecasting for the Agriculture Economy of Computational Social Systems Li, Xuelan Li, Xiao Jiang, Jiyu Comput Intell Neurosci Research Article In the vision of smart cities, everything is highly connected with the aid of computational intelligence. Therefore, the cyber-physical society has been named a computational social system for a long time. Due to the high relation with vast populations' national livelihood, agriculture will still serve as a core industry in the national economy. As a result, this study focused on an efficient forecasting method for the agriculture economy. In recent years, the conception of deep intelligence has received overall prevalence in academia because of its excellent performance in implementing intelligent information processing tasks. Hence, this paper utilized deep intelligence driven by neural networks and managed to investigate an efficient prediction method for the agriculture economy of computational social systems. To fit the time-series forecasting scene of the long-term development of the agriculture economy, the convolutional neural network model is slightly improved by revising its parallel structure into the recurrent format. Finally, simulations on realistic datasets are carried out to evaluate the proposed forecasting method. Hindawi 2022-09-27 /pmc/articles/PMC9532071/ /pubmed/36203731 http://dx.doi.org/10.1155/2022/2854675 Text en Copyright © 2022 Xuelan Li et al. 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 Li, Xuelan Li, Xiao Jiang, Jiyu Deep Intelligence-Driven Efficient Forecasting for the Agriculture Economy of Computational Social Systems |
title | Deep Intelligence-Driven Efficient Forecasting for the Agriculture Economy of Computational Social Systems |
title_full | Deep Intelligence-Driven Efficient Forecasting for the Agriculture Economy of Computational Social Systems |
title_fullStr | Deep Intelligence-Driven Efficient Forecasting for the Agriculture Economy of Computational Social Systems |
title_full_unstemmed | Deep Intelligence-Driven Efficient Forecasting for the Agriculture Economy of Computational Social Systems |
title_short | Deep Intelligence-Driven Efficient Forecasting for the Agriculture Economy of Computational Social Systems |
title_sort | deep intelligence-driven efficient forecasting for the agriculture economy of computational social systems |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532071/ https://www.ncbi.nlm.nih.gov/pubmed/36203731 http://dx.doi.org/10.1155/2022/2854675 |
work_keys_str_mv | AT lixuelan deepintelligencedrivenefficientforecastingfortheagricultureeconomyofcomputationalsocialsystems AT lixiao deepintelligencedrivenefficientforecastingfortheagricultureeconomyofcomputationalsocialsystems AT jiangjiyu deepintelligencedrivenefficientforecastingfortheagricultureeconomyofcomputationalsocialsystems |