Research on grape price forecasting of Henan Province based on particle swarm optimization random forest algorithm
Henan Province is one of the important grape planting bases in China,with extensive grape planting area and abun-dant yield.Therefore,it is very important to predict the price of grapes in Henan Province.In order to improve the accuracy and sta-bility of grape price prediction,a PSO-RF prediction model is proposed in this paper.In this model,particle swarm optimization(PSO)is used to optimize the depth of decision tree in random forest,select the optimal number of predictors,and further obtain the optimal combination of predictors.The experimental results show that compared with the single random forest prediction model,the PSO-RF model has higher prediction accuracy,MAE is only 0.0095,R2 is 0.968.Therefore,the PSO-RF prediction model can make a more accurate prediction of grape price in Henan Province.