Volume 37 Issue 1
Jan.  2017
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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]. Journal of Space Science, 2017, 37(1): 1-7. doi: 10.11728/cjss2017.01.001
Citation: 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]. Journal of Space Science, 2017, 37(1): 1-7. doi: 10.11728/cjss2017.01.001

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

doi: 10.11728/cjss2017.01.001
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)

  • Received Date: 2015-12-31
  • Rev Recd Date: 2016-04-08
  • Publish Date: 2017-01-15
  • 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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