A real time K-indices scaling method based on radial basis neural network

作者：Qi Wei^*; Wang Xiu Fang; Li Xi Hai; Liu Dai Zhi

来源：Chinese Journal of Geophysics, 2010, 53(1): 147-155.

DOI：10.3969/j.issn.0001-5733.2010.01.016

• Geomagnetic field
• K index
• Radial basis neural network
• FMI method
• Solar regular variation

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.

• 出版日期2010-1
• 单位中国人民解放军火箭军工程大学