An Improved Prediction Model of Pig Price
Gong Xiaohui *
North China University of Water Resources and Electric Power, Zhengzhou, Henan, China.
Cao Chuang
North China University of Water Resources and Electric Power, Zhengzhou, Henan, China.
*Author to whom correspondence should be addressed.
Abstract
In many agricultural products, pig price fluctuation has a significant impact on price level and consumer price index, so accurate prediction of pig price is of great significance for pig market research and production. In order to predict the price of pigs more accurately in the short term, Attention-LSTM prediction model (a short-term memory neural network based on attention mechanism) is established. The results show that: compared with the traditional LSTM forecasting model, the Attention-LSTM model has higher prediction accuracy, and this model has a good effect on the short-term prediction of pig prices.
Keywords: Agricultural, pig price, prediction, attention mechanism