摘要
依据秋白菜受冻的日最低气温指标,利用本溪市1957~2008年逐日最低气温资料,应用模糊数学隶属度函数预测日最低≤-7℃的初日趋势,建立多元回归模型预测日最低气温≤-7℃初日,为指导秋白菜适时收获、合理安排上期提供科学的气象依据。
Based on the daily minimum temperature indicator of cold autumn cabbage,using the data of annual daily minimum temperature in Benxi City during 1956-2008,the fuzzy mathematics membership function was used to predict the initial day trend with the daily minimum temperature of less than or equal-7 ℃.The multiple regression model was established to predict the initial days with the daily minimum temperature of less than or equal-7 ℃,in order to provide scientific weather basis for guiding the timely harvest of autumn cabbage and reasonable arrangements for the sale.
出处
《安徽农业科学》
CAS
北大核心
2010年第18期9387-9388,9399,共3页
Journal of Anhui Agricultural Sciences
关键词
隶属度函数
回归预测
秋白菜适宜收获
Membership function
Regression prediction
Suitable harvest of autumn cabbage