摘要
阐述了应用卡尔曼滤波法和BP网络法进行天气预报建立模型的基本原理,通过具体的预报试验说明两种自适应方法建模明显优于传统的逐步回归方法建模,为数值天气预报产品的统计解释应用提供了新思路。
In this paper, principles of weather forecast modeling based on Kalman filtering and BP neural networks are introduced. Forecast results indicated that weather forecast modeling based on Kalman filtering and BP neural networks was superior to that based on stepwise regression analysis, and this provide new way for statistical interpretation of mathematical forecast products.
出处
《孝感学院学报》
2007年第3期80-83,共4页
JOURNAL OF XIAOGAN UNIVERSITY
关键词
线性回归
BP网络
天气预报
自适应算法
stepwise regression
BP neural networks
weather forecast
adaptive algorithm