首页 >  2003, Vol. 7, Issue (4) : 1993-2002

摘要

全文摘要次数: 3582 全文下载次数: 24
引用本文:

DOI:

10.11834/jrs.20030402

收稿日期:

2003-06-05

修改日期:

2003-06-07

PDF Free   HTML   EndNote   BibTeX
SARS疫情预测预报中的分段非线性回归方法
1.北京师范大学 数学系,数据统计与数据分析,北京 100875;2.北京师范大学 遥感与GIS研究中心,北京 100875;3.中国科学院 遥感应用研究所,北京 100101
摘要:

介绍了几种对累计SARS疫情预测预报中的非线性增长曲线模型,说明了Richards增长曲线在这次SARS疫情预测预报中合理性和可行性,由此建立了累计SARS疫情预测预报中的非线性回归点模型。并具体对北京SARS疫情进行了跟踪预测预报,包括整体和分时间段的预测预报,获得了北京SARS疫情随时间的预测预报结果,说明了北京4月底的一系列控制措施对北京SARS疫情所带来的影响,为进一步的后续研究打下了良好基础。

Nonlinear Regression in SARS Forecasting
Abstract:

This paper introduces some kinds of nonlinear growth curve for forecasting cumulative SARS patients, it is shown that the Richards curve is reasonable and flexible in this SARS forecasting. The nonlinear growth curve regression model is established for forecasting cumulative SARS patients.Specifically,the SARS situation forecasting in Beijing is made well which includes forecasting based on comsecutive and piecewise time fitting. It means some control policies in Beijing at the end of this April play important role for anti-spread of SARS,and also provides a good basis for future works.

本文暂时没有被引用!

欢迎关注学报微信

遥感学报交流群 分享按钮