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C. Chen, Z. S. Wu, S. J. Sun, et al., “Forecasting of Ionospheric foF2 in China Using Neural Network. Chin. J. Space Sci., Vol. 31, No. 3, 2011, pp. 304-310.

has been cited by the following article:

• TITLE: Application of Grey Theory to Ionospheric Short-term Forecasting

  AUTHORS: Yao Xiao, Zhonghui Gan, Yunjiang Liu, Man Li

  KEYWORDS: Ionosphere; Short-term Forecasting; Grey Theory

  JOURNAL NAME: Communications and Network, Vol.5 No.3C, November 7, 2013

  ABSTRACT: By analysis of historical data of the ionosphere, it is suggested to apply grey theory to ionospheric short-term forecasting, grey range information entropy is defined to determine the optimum grey length of the sample sequence, the prediction model based on residual error is constructed, and the observation data of multiple ionospheric observation stations in China are adopted for test. The prediction result indicates that the average grey range information entropy calculation results reflect the cyclical effects of solar rotation, precision of the forecasting method in high latitudes is higher than low latitudes, and its error is large relatively in more intense solar activity season, the effect of forecasting 1 day in advance of average relative residuals are less than 1 MHz, the average precision is more than 90%. It provides a new way of thinking for the ionospheric foF2 short-term forecast in the future.