Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F_(10.7) |
| |
Affiliation: | 1. School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044;2. Key Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029;3. School of Science, Harbin Institute of Technology, Shenzhen 518055 |
| |
Abstract: | The solar 10.7 cm radio flux,F_(10.7),a measure of the solar radio flux per unit frequency at a wavelength of 10.7 cm,is a key and serviceable index for monitoring solar activities.The accurate prediction of F_(10.7) is of significant importance for short-term or long-term space weather forecasting.In this study,we apply Back Propagation(BP)neural network technique to forecast the daily F_(10.7)based on the trial data set of F_(10.7) from 1980 to 2001.Results show that this technique is better than the other prediction techniques for short-term forecasting,such as Support Vector Regression method. |
| |
Keywords: | |
本文献已被 CNKI 等数据库收录! |
| 点击此处可从《空间科学学报》浏览原始摘要信息 |
|
点击此处可从《空间科学学报》下载全文 |
|