Research On Grain Yield Prediction In Jilin Province Based On Big Data

In the 1920 s,when the world was faced with the sudden COVID-19 epidemic,people’s awareness of food security was improved.At the same time,stable food production was an indispensable strategic guarantee to promote the formation of China’s "new development pattern".Jilin Province is the main base of national grain production and also the main base of national grain production.It has a good development foundation and plays a crucial role in ensuring national food security.In the context of the interweaving,collaboration,and fusion of the three dimensional spaces of "information space","physical space",and "human society",massive,multi-source,and real-time data that can reflect the situation of food security are constantly emerging.Based on this,big data effectively analyze the factors of food production and accurately predict the situation of food production,It is an important way to ensure the safety of food production.This article obtains information through big data and takes the grain yield of Jilin Province as the research object to carry out the prediction of grain yield in Jilin Province.In order to understand its changing trends in advance,formulate corresponding countermeasures,enhance its comprehensive strength,achieve increased production and efficiency,and provide a basis for ensuring food security.(1)Analysis and Research on the Factors Influencing Grain Production in Jilin ProvinceObtain the required data from the target database,analyze the grain yield and related influencing factors in Jilin Province from 2012 to 2021,and select 12 factors that affect grain yield;By using principal component analysis to analyze relevant data,the main factors affecting grain yield in Jilin Province were identified,providing a basis for subsequent prediction research.(2)Research on Short Term Prediction of Grain Yield in Jilin ProvinceTo solve the problems of traditional prediction models that often use single factor analysis and low detection accuracy,and fully leverage the advantages of multiple regression in short-term prediction,correlation analysis is conducted using factors obtained from big data to determine the correlation between grain yield and its influencing factors,and a short-term prediction model for grain yield based on multiple regression is established;The prediction results indicate that the accuracy of the prediction is high and can achieve short-term prediction of grain yield.(3)Long term prediction of grain yield in Jilin ProvinceTo address the impact of uncertain factors such as small sample size and poor data,and to achieve long-term prediction when conditions are lacking,a long-term prediction model for grain yield based on grey GM(1,1)is established,taking into account the advantages of low sample demand and reasonable prediction results in grey GM(1,1)data;The prediction results indicate that the fitting degree of the prediction is high and can achieve long-term prediction of grain yield.The establishment of a grain yield prediction model based on big data has achieved short-term and long-term predictions of grain yield in Jilin Province,providing a certain theoretical basis for improving the analysis and prediction of grain yield in the macroeconomic regulation of the agricultural market.Furthermore,policies that are suitable for market economic needs can be formulated to improve the efficiency of macroeconomic regulation in Jilin Province.