PREDICTING THE MONTHLY MEAN VALUES OF f₀F₂ BY USING THEARTIFICIAL NEURAL NETWORK

A method to predict the monthly mean Values of f₀F₂ is presented in this paper. The analysis results of monthly values of f₀F₂ indicate that the characteristic of this ionospheric parameter change with different month and different year. Based on it, the f₀F₂ monthly mean value is predicted by taking sufficient data of many yeas into account and improved the predicting method. Compared with the conserved data, the average error is less than 0.34MHz. Then, the fraction characteristic of ionosphere has been set forth by using the theory of fraction and the fraction dimension of the f₀F₂ monthly mean value has been acquired. Based on it, 3 parameters are selected to predict the f₀F₂ monthly mean value for different year, thus, the predicted technology is improved further. Compared with the conserved data, the average error is less than 0.3 MHz.