摘要
】对四川省稻飞虱常发区的灯下、田间稻飞虱资料及４～６月各旬的温度、降水量、相对湿度等因子，用神经网络的ＢａｃｋＰｒｏｐａｇａｔｉｏｎ算法进行分析，并对发生程度试报，效果较好。
The Back Propagation algorithm of the neural network was used to analyse the data of field occurrence of rice planthoppers, the temperature difference in early, middle and late April, May and June, precipitation and relative humidity in the infested areas of Sichuan province. Based on such an analysis, a trial forecast was made of the occurrence of the pest and gave relatively satisfactory result.
出处
《西南农业大学学报（自然科学版）》
CSCD
1996年第6期583-587,共5页
Journal of Southwest Agricultural University
关键词
飞虱科
神经网络
预测
水稻
BP算法
稻飞虱
planthopper
neural networks
Back Propagation algorithm
forecasting
paddy
