摘要
目的 应用人工神经网络的原理和方法 ,探讨在干旱灾害条件下影响伤寒副伤寒流行的关键气象因子 ,建立旱灾地区传染病疫情的BP神经网络模型 ,并评价模型的拟合效果。方法 利用Matlab 6 5软件对人工神经网络BP模型进行构建、训练及模拟。结果 伤寒副伤寒发病率回代平均误差率和R2 分别为 0 84%和 0 9999。自变量对输出的贡献量分析结果显示 ,平均蒸发量和平均气压对于伤寒副伤寒发病率影响最大。结论 伤寒副伤寒与气象因素关系的BP神经网络模型拟合效果较好 。
Objective To investigate the relations between meteorological factors and typhoid fever and paratyphoid fever,Back Propagation artificial neural network model was built and evaluated.Methods Back Propagation artificial neural network model was built by Matlab,version 6.5.Results The Mean Error Rate and R 2 was 0 84% and 0 999 respectively. The mean evaporation and mean air pressure were correlation to the incidence of typhoid fever and paratyphoid fever.Conclusion The BP Neural Network model has practical value to popularize in simulation of situation between meteorological factors and infectious disease in drought area.
出处
《中国卫生统计》
CSCD
北大核心
2004年第3期165-167,共3页
Chinese Journal of Health Statistics
基金
国家自然基金资助 (课题编号 :30 1 70 833)
关键词
干旱地区
副伤寒
气象因素
BP神经网络模型
神经网络
神经冲动
Meteorological factors
Entomoplious disease
Typhoid fever and paratyphoid fever
Back-propagation neural network