| Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F10.7 |
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| 作者姓名： | XIAO Chao CHENG Guosheng ZHANG Hua RONG Zhaojin SHEN Chao ZHANG Bo HU Hui |
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| 作者单位： | 1. School of Mathematics and Statistics, Nanjing University of Information Science and Technology, Nanjing 210044; |
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| 基金项目： | Supported by the National Natural Science Foundation of China （41231066），the Foundation for Ministry of Science and Technology of China （2011CB811404），the Specialized Research Fund for State Key Laboratories of the CAS，and the Scientific Research Staring Foundation for Nanjing University of Information Science and Technology （2013x030） |
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| 摘 要： | The solar 10.7 cm radio flux，F10.7，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 F10.7 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 F10.7 based on the trial data set of F10.7 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.
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| 关 键 词： | F10.7 Back Propagation(BP) Forecast |
| 收稿时间： | 2015-12-31 |
Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F_(10.7) |
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| XIAO Chao,CHENG Guosheng,ZHANG Hua,RONG Zhaojin,SHEN Chao,ZHANG Bo,HU Hui.Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F10.7[J].Chinese Journal of Space Science,2017,37(1):1-7. |
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| Institution: | 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 |
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| 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. |
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