三种热量指数预测方法在热量年型预测中的应用

• 作 者: 王美玉 王冬妮 郭春明 曲思邈 苏丽欣
• 机 构: 吉林省气象局,长春,130062;吉林省气象科学研究所,长春130062;长白山气象与气候变化吉林省重点实验室,长春130062
• 出 处: 东北农业科学
• 发表日期: 2018年1期
• 关键词: Heat index Maize Stepwise regression model Gray model Mean generating function

以逐日热量指数为基础,采用逐步回归模型、灰色模型、均生函数模型在吉林省各区域建立逐月热量指数模型.结果显示:三种预测模型的回代平均准确率均在96％以上,外推准确率都在94％以上,各模型均可以较准确地预测各个地区的玉米热量指数,其中均生函数是这三种模型中预测效果最好的.“,”Based on daily heat index,the monthly heat index model was established using methods of the stepwise regression model,the gray model and the mean generating function model in every region of Jilin Province.The results showed that the average accuracy of the back substitution tests of three models were over 96％,the average accuracy of the extrapolate results of three models were over 94％,each model was able to forecast corn heat index preferably,and the mean generating function model was the best one.