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Estimation of Ionospheric Electron Density Physical Perdiction Model Parameters Using Artificial Neural Network
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Mohammad Mahdi Kakanj   , Yazdan Amerian * , Hany Mahbuby |
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Abstract: (261 Views) |
The ionosphere, the upper layer of the earth's atmosphere, contains free ions and electrons, which greatly impact radio and satellite signal transmission. Correcting the observations of global navigation satellite systems (GNSS) to increase the accuracy of positioning, improving the design and performance of radio communication systems, correcting the effects of the ionosphere to improve the accuracy of radar data, better understanding atmospheric and spatial changes due to storms, solar and geomagnetic activities are some examples which demonstrate the considerable importance of ionospheric electron density (Ne) prediction. Electron density prediction is technically superior to total electron content (TEC), providing more accurate information regarding the distribution of electrons at different heights of the ionosphere. This research aims to predict the ionospheric electron density by predicting the parameters of the continuity equation using an artificial neural network. This study, which was conducted in three broad phases, predicts the electron density of the ionosphere for Iran on the 129th day of 2016. Firstly, the parameters of the continuity equation are computed using the electron density obtained from the International Ionosphere Reference (IRI), a restricted linear regression procedure, and the sun's radiant flux on grid points spaced 0.5 degrees apart. Together with the input data from the 123rd to 128th days of 2016. In the second phase, these values are used in the artificial neural network to train a feed-forward neural network. In the third stage, the ionosphere's electron density is predicted by inserting the artificial neural network's predicted parameters into the continuity differential equation. After analyzing the data, it was determined that the average RMS value of the difference between the IRI electron density and the predicted electron density on the 129th day was 1.0943×1011 for three hours, 2.3733×1010 for two hours, and 1694.5×1010 for two hours. |
Article number: 9 |
| Keywords: Artificial neural network, Ionospheric electron density, Total electron content, Ionospheric continuity equation, IRI |
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Full-Text [PDF 866 kb]
(150 Downloads)
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Type of Study: Research |
Subject:
Geo&Hydro
Received: 2024/08/9
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