• 责任者：Qi Wei (The Second Artillery Institute of Engineering ; Xi′an 710025 ; China) ; Wang Xiufang
• 刊名：Chinese Journal of Geophysics
• 出版年：2010
• 卷期：53(1)
• 关键词：地磁场长期变化 ; secular variations of geomagnetic field
• 页码：p.147-155
• 图表：illus., 27 refs.
• 分类号：0400
• issnNo：ISSN0001-5733
• isbnNo：CN11-2074/P

The difficulty to scale K-indices is how to identify the solar regular variation (S_R) and FMI method is a verified effective method for appropriate elimination of S_R. However FMI method is not able to give K-indices in real time because there is always one day′s delay to acquire S_R. To solve this problem we propose a new method based on radial basis neural network which is able to give real time K-indices. Firstly the solar regular variations of H element is obtained by the modified FMI method and then radial basis neural network is used to model this time series, and finally according to the model output and the current mean minute value of H element K-indices are scaled in real time. Experiments show that this method can give real-time solar regular variations with a standard error of 3.8598 nT. The comparison between the K-indices scaled by FMI-H method with one day′s delay and the real-time K-indices confirm this method: 69.8% are in agreement，0.77% differ more than one unit.