Research on correlation analysis and prediction model of agricultural climate factors based on machine learning

This article uses machine learning technology to analyze the correlation of climate factors that affect crop yields, and conduct prediction comprehensive evaluation guide agricultural production. paper selects early rice crops in Guangxi as research object. Based on climatic data planting areas from 1990 2017, a cart decision tree is constructed generate random forest model between yield each growth period, obtain various periods The ranking importance yield, thus forming basis for calculating weights period rice; based Guilin, 2008 April July predicted by long short-term memory network Guilin's 2018.