基于随机森林的玉米储藏试验及温度预测  

Storage Experiment and Temperature Prediction of Corn Based on Random Forest

作　　者：陈思羽[1] 徐爱迪 刘春山[1] 朱红媛 李捷涵 王贞旭 吴文福[2] Chen Siyu;Xu Aidi;Liu Chunshan;Zhu Hongyuan;Li Jiehan;Wang Zhenxu;Wu Wenfu(College of Mechanical Engineering,Jiamusi University,Jiamusi 154000,China;College of Biological and Agricultural Engineering,Jilin University,Changchun 130002,China)

机构地区：[1]佳木斯大学机械工程学院,黑龙江佳木斯154000 [2]吉林大学生物与农业工程学院,长春130002

出　　处：《农机化研究》2023年第4期207-210,共4页Journal of Agricultural Mechanization Research

基　　金：黑龙江省教育厅基础研究项目(2018-KYYWF-0929)。

摘　　要：为了提高粮食储藏过程中对粮情的精准测控,基于自建试验仓对玉米进行了储藏试验,并利用随机森林法建立了玉米储藏过程中的温度预测模型。通过分层分析粮堆内部温度变化,初步构建了预测模型,结果表明:第1层随机森林训练集的准确率约为0.99,测试集约为0.65;第2层随机森林训练集的准确率约为0.99,测试集约为0.58;第3层随机森林模型训练集为0.99,得出测试集约为0.33;第4层随机森林训练集的准确率约为0.99,测试集约为0.95。根据初步建立的随机森林模型状况分析得出:第1~4层均存在过拟合、泛化误差高及方差高等现象。通过对各层模型参数的优化,最终确定了基于随机森林的玉米粮堆温度预测模型,结果表明:粮堆内部各层温度检测数据利用随机森林法在训练集与测试集上均表现良好,在大样本数据处理过程中,模型较准确,可为粮堆储藏粮情精准测控提供重要依据。In order to improve the accurate measurement and control of grain situation in the process of grain storage,this paper carried out storage test on corn based on self-built test bin and established a temperature prediction model applied to corn storage process by using random forest method.The results showed that the accuracy of the first random forest training set was about 0.99,the test set was about 0.66,the accuracy of the second random forest training set was about 0.99,the test set was about 0.58.The training set of the third layer random forest model is 0.99,and the test set is about 0.38.The accuracy of the fourth layer random forest training set is about 0.99,and the test set is about 0.95.According to the preliminary analysis of the random forest model,over-fitting,high generalization error and high variance exist in the first,second,third and fourth layers.By optimizing the model parameters of each layer,the prediction model of corn stack temperature based on random forest was finally determined.The results showed that the random forest method performed well in both the training set and the test set.In the process of large sample data processing,the model is more accurate,and provides an important basis for accurate measurement and control of grain storage situation.

关 键 词：玉米 储藏 随机森林 温度预测 

分 类 号：S379.2[农业科学—农产品加工]