An Aquatic Product Price Forecast Model Using VMD-IBES-LSTM Hybrid Approach

Junhao Wu, Yuan Hu, Daqing Wu () and Zhengyong Yang
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Junhao Wu: College of Economics and Management, Shanghai Ocean University, Shanghai 201306, China
Yuan Hu: College of Economics and Management, Shanghai Ocean University, Shanghai 201306, China
Daqing Wu: College of Economics and Management, Shanghai Ocean University, Shanghai 201306, China
Zhengyong Yang: College of Economics and Management, Shanghai Ocean University, Shanghai 201306, China

Agriculture, 2022, vol. 12, issue 8, 1-26

Abstract: Changes in the consumption price of aquatic products will affect demand and fishermen’s income. The accurate prediction of consumer price index provides important information regarding the aquatic product market. Based on the non-linear and non-smooth characteristics of fishery product price series, this paper innovatively proposes a fishery product price forecasting model that is based on Variational Modal Decomposition and Improved bald eagle search algorithm optimized Long Short Term Memory Network (VMD-IBES-LSTM). Empirical analysis was conducted using fish price data from the Department of Marketing and Informatization of the Ministry of Agriculture and Rural Affairs of China. The proposed model in this study was subsequently compared with common forecasting models such as VMD-LSTM and SSA-LSTM. The research results show that the VMD-IBES-LSTM model that was constructed in this paper has good fitting results and high prediction accuracy, which can better explain the seasonality and trends of the change of China’s aquatic product consumer price index, provide a scientific and effective method for relevant management departments and units to predict the aquatic product consumer price, and have a certain reference value for reasonably coping with the fluctuation of China’s aquatic product market price.

Keywords: aquatic products price forecast; VMD; IBES; LSTM; hybrid model (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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