Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity <i>F</i><sub>10.7</sub>

XIAO Chao; CHENG Guosheng; ZHANG Hua; RONG Zhaojin; SHEN Chao; ZHANG Bo; HU Hui

doi:10.11728/cjss2017.01.001

Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F_10.7

doi: 10.11728/cjss2017.01.001

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

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）

详细信息

通讯作者:
XIAO Chao,E-mail:xc@nuist.edu.cn

中图分类号: P353
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出版历程
- 收稿日期: 2015-12-31
- 修回日期: 2016-04-08
- 刊出日期: 2017-01-15

Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F_10.7

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

Funds:

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)

摘要

摘要: 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.
- F_10.7 /
- Back Propagation(BP) /
- Forecast
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.
- F_10.7 /
- Back Propagation(BP) /
- Forecast

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参考文献(17)

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Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F_10.7

doi: 10.11728/cjss2017.01.001

通讯作者:
XIAO Chao,E-mail:xc@nuist.edu.cn

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Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F_10.7

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Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F10.7

doi: 10.11728/cjss2017.01.001

通讯作者: XIAO Chao,E-mail:xc@nuist.edu.cn

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出版历程

Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F10.7

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出版历程

目录

Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F_10.7

通讯作者:
XIAO Chao,E-mail:xc@nuist.edu.cn

Using Back Propagation Neural Network Method to Forecast Daily Indices of Solar Activity F_10.7