摘要
运用逐步回归分析方法．建立了多元线性的中期预报方程．入选的自变量有初始病情ｙ０、年平均温度ｔ１、温湿比ｘ１和湿雨比ｘ２ ４个因子．该模型可以预测第二年的病情指数。根据病情指数随时间增长的趋势．选用灰色方法建立了ＧＭ（１，１）数学模型。模型中的二个参数ａ＝０．３７８６，ｕ＝８．４８５ ３．按距离贴近原则。可作出中长期预报。
Using stepwise variable selection method, the authors set up the multi-variant linear regression forecasting equation, initial disease index y0. annual average temperature ti. the ratio of temperature to relative humidity xl and the ratio of relative humidity to precipitation x2 are selected into the model. it can predict the next year's disease index. Use grey method. the authors set up the GM(l. l) model. the values of the two parameters in the model .are:a= -0. 378 6. u=8. 485 3. According to the rule nestled up against the distance. it can make middle or long period forecast.
出处
《东北林业大学学报》
CAS
CSCD
北大核心
2001年第3期120-122,共3页
Journal of Northeast Forestry University
基金
国家"九五"科技攻关子专题
关键词
杨树
冰核细菌溃疡病
预测预报
Poplar
Ice nucleation active bacterial canker
Forecast
