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山东省小麦病虫害分区预测模型的研究
引用本文:迟新之,原永兰.山东省小麦病虫害分区预测模型的研究[J].山东农业大学学报(自然科学版),1995,26(1):89-97.
作者姓名:迟新之  原永兰
作者单位:山东省植物保护总站
摘    要:对影响1982 ̄1991年山东省及各类型区小麦病虫发生量(预报量y)的环境因素(预报因子x1),在一元线性回归初选的基础上,经逐步回归、逐步判别、多元回归和多级判别分析进行精选,共建立全省和各类型区预测模型186个,从中筛选出最优预测模型30个,于1993年和1994年应用,平均预测准确率达90%以上。

关 键 词:小麦  病虫害  预测  数学模型  山东

STUDY ON FORECASTING MODEL OF DISTRICTS OF WHEAT DISEASES AND INSECT PESTS IN SHANDONG PROVINCE
Chi Xinzhi,Yuan Yonglan,Guo Zhenzong,Yang Wanhai,Liu Jingdong, Feng Ling.STUDY ON FORECASTING MODEL OF DISTRICTS OF WHEAT DISEASES AND INSECT PESTS IN SHANDONG PROVINCE[J].Journal of Shandong Agricultural University,1995,26(1):89-97.
Authors:Chi Xinzhi  Yuan Yonglan  Guo Zhenzong  Yang Wanhai  Liu Jingdong  Feng Ling
Abstract:in this paper, the authors not only sorted out the systematic monitoring data anwheat diseases and insect pests and factors affecting their occurrence, but also analysed theforcasting targets y(occurring amount) and different combinations of forecastingfacts xj(j = 1, 2, """, m) that affecting the occurrence of wheat diseases and insect pests byadopting some statistic methods such as stepwise regression, discrimination step by step,multivariate regression and multiplestage discrimination. They established 186 predictingmodels of wheat diseases and insect pests in different types areas or over all provincethrough calculation different values of FI and F2 of stepwise regression and discriminationstep by step, importing constantly main factors that posses fine interrelation, eliminationsecondary factors that posses poor interrelation, choosing precisely foreasting factors onthe basis of primary choose with single factor linear regression. They screened out 30 "the finest" predicting mathematical models according to the ratio of back-checking with historymaterial of variety models and stabilities status. The average predicting accuracy is 90%through applying in 1993 and 1994.
Keywords:wheat diseases and insect pests  forecast  mathematical model  
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