Analysis of Influencing Factors of Pork Price Fluctuation and Prediction Modeling Based on Multidimensional Association Rules

Abstract

【Objective】China is the main country in pork production and consumption. In recent years, pork price fluctuations have shown the trend of accelerating frequency and increasing amplitude. The fluctuation of pork price not only increases the risk of farmers' income, but also affects the living of the general public. Correctly identifying the influencing factors of pork price fluctuations and making accurate predictions help to guarantee the well-functioning of the market.【Method】The multi-dimensional association rules were used to quantitatively analyze the correlation and influencing degree of 16 influencing factors in five main aspects including the industrial chain of pig breeding and processing, market of substitutes, changes in macroeconomic environment, emergencies and international market environment with pork price fluctuations. High correlation factors selected by mining were used as model input variables, and the support vector regression machine was used to construct a multi-step prediction model for pork price fluctuations.【Result】The top three factors most related to pork price fluctuations are pig epidemics, pig prices and piglet prices, with confidence levels of 1.00, 0.93 and 0.82 respectively. The top three factors have the greatest impact on pork prices are pig epidemics, pork production and pork supplied to the market, with the improvement degrees of 1.84, 1.67 and 1.67, respectively. Compared with the baseline prediction model, with 12 highly correlated influencing factors as model inputs, the Root Mean Square Error (RMSE) is reduced by 29.11%, and the Mean Absolute Percentage Error (MAPE) is reduced by 16.00%.【Conclusion】The use of multi-dimensional association rules for variable selection not only reduces the number of variables, but also effectively improves the prediction accuracy. Given the vital influence that pig epidemic imposes on price volatility, authorities should raise the awareness of risk prevention of animal diseases.

Keywords

• pork price
• influencing factor
• multi-dimensional association rule
• support vector regression
• price forecasting
• pig epidemic