Prediction of Soybean Price Trend via a Synthesis Method With Multistage Model

Zhiling Xu, Hualing Deng, Qiufeng Wu

Source Title: International Journal of Agricultural and Environmental Information Systems (IJAEIS)12(4)

ISSN: 1947-3192|EISSN: 1947-3206|EISBN13: 9781799861614|DOI: 10.4018/IJAEIS.20211001.oa1

MLA

Xu, Zhiling, et al. "Prediction of Soybean Price Trend via a Synthesis Method With Multistage Model." IJAEIS vol.12, no.4 2021: pp.1-13. http://doi.org/10.4018/IJAEIS.20211001.oa1

APA

Xu, Z., Deng, H., & Wu, Q. (2021). Prediction of Soybean Price Trend via a Synthesis Method With Multistage Model. International Journal of Agricultural and Environmental Information Systems (IJAEIS), 12(4), 1-13. http://doi.org/10.4018/IJAEIS.20211001.oa1

Chicago

Xu, Zhiling, Hualing Deng, and Qiufeng Wu. "Prediction of Soybean Price Trend via a Synthesis Method With Multistage Model," International Journal of Agricultural and Environmental Information Systems (IJAEIS) 12, no.4: 1-13. http://doi.org/10.4018/IJAEIS.20211001.oa1

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Abstract

Soybean is an important crop, so it is very important to forecast soybean price trend, which can stabilize the market. This paper presents a Synthesis Method with Multistage Model (SMwMM) in order to identify and forecast soybean price trend in China. In the previous work,Toeplitz Inverse Covariance-based Clustering(TICC) has been applied to cluster the prices of four variables. The research have found that there are four patterns in soybean market price, which could be explained by economic theory. This paper consider four patterns as market risk levels. Based on the clustering results, we used Long short-term memory(LSTM) to forecast the prices of these four variables. Multivariate long short-term memory(MLSTM) is then used to classify soybean price to determine level of risk . Experimental results show that :(1)The LSTM model has achieved great fitting effect and high prediction accuracy;(2) The performance of MLSTM-FCN and MALSTM-FCN is better than that of LSTM-FCN and ALSTM-FCN. Furthermore,MALSTM-FCN had the higher accuracy than MLSTM-FCN, which reached 76.39%.