Abstract
Wisdom agriculture is a high-level development stage of modern agriculture, which is also one of the key areas of development of national Internet planning. A large number of scientific and technological innovation technology used in agricultural development, including communication technology, automation control systems, and wisdom of agricultural management, which is a complex and unpredictable time series, most of the research methods are based on the linear model, ignoring the nonlinear factors, resulting in the prediction accuracy is not high. In this study, the ARIMA model was used to linearly model the agricultural management time series, and then the nonlinear part of the agricultural management time series was modelled by SVM. Finally, the comprehensive prediction results of the two models were obtained. In addition, this paper combined with intelligent agriculture multi-information fusion technology, which is based on corn planting management empirical analysis in Jiangsu Province. The experimental results show that the combined model is more accurate than the single model, BP neural network prediction has higher precision, and the advantages of the two models are played, and the model is better Agricultural production assessment and adaptation research which need to be applied.
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22 December 2022
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s10586-022-03925-4
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Wen, Q., Wang, Y., Zhang, H. et al. RETRACTED ARTICLE: Application of ARIMA and SVM mixed model in agricultural management under the background of intellectual agriculture. Cluster Comput 22 (Suppl 6), 14349–14358 (2019). https://doi.org/10.1007/s10586-018-2298-5
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DOI: https://doi.org/10.1007/s10586-018-2298-5