摘要
通过对脑卒中发病率与气象因素关系系统的统计分析,显示出气温、气压、相对湿度与发病率之间均存在显著的二次相关关系,以此建立线性回归模型和BP人工神经网络模型,得到发病率与气象因素间关系的定量描述,并与实际发病率进行比较,得到比较准确的预测模型,具有较好的现实推广意义.
In this paper, systematic statistical analysis were applied to reveal the relationship between the incidence of stroke and meteorological factors and the results displayed that temperature, atmospheric pressure, relative humidity and morbidity have a significant quadratic correlation with the incidence of stroke. A linear regression model and a BP artificial neural network model were established. The quantitative description made from these models about the correlation between the incidence and meteorological factors was compared with the actual incidence, which was facilitated to build accurate predictive models. Research in this paper also provides advice to the population with high risk of stroke.
出处
《广西工学院学报》
CAS
2013年第4期76-79,共4页
Journal of Guangxi University of Technology
基金
重庆市高等教育教学改革研究项目(103433)资助
关键词
发病率
环境因素
统计分析
相关系数
回归分析
BP神经网络
morbidity
environmental factors
statistical analysis
correlation coefficient
regression analysis
BP neural network
