TEC Prediction Model using Neural Networks over a Low Latitude GPS Station
D. Venkata. Ratnam1, B. Venkata Dinesh2, B. Tejaswi3, D. Praveen Kumar4, T. V. Ritesh5, P. S. Brahmanadam6, G. Vindhya7
1D.Venkata Ratnam, Associate Professor, ECE Dept, KL University, Guntur Dt, AP, India.
2B.Venkata Dinesh, Student, ECE Dept KL University, GUNTUR Dt, AP, India.
3B. Tejaswi, Student, ECE Dept JNTU Kakinada, India
4D. Praveen Kumar, Student, ECE Dept, KL University, Guntur, India
5T. V. Ritesh, Student, ECE Dept, KL University, Guntur, India.
6P. S. Brahmanadam, , Associate Professor, ECE Dept, KL University, Guntur Dt, AP, India.
7G.Vindhya, Asst Professor,ECE Dept, Osmania University College for Women, Koti, Hyderabad.
Manuscript received on April 11, 2012. | Revised Manuscript received on April 14, 2012. | Manuscript published on May 05, 2012. | PP: 517-521 | Volume-2 Issue-2, May 2012 . | Retrieval Number: B0632042212 /2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Ionospheric nowcasting and forecasting tools are necessary for high precision applications in equatorial regions such as India and Brazil, etc. An algorithm capable of predicting the ionospheric behavior in advance can be used to setup early warnings for GPS applications. In this paper, Neural Network (NN) model using back propagation algorithm is implemented over a low latitude GPS station (Hyderabad). The preliminary results indicate that, NN model values are closely following with actual data. It is found that, the prediction error is varied maximum up to 1TECU. Advanced NN models would be useful for forecasting ionospheric characteristics in a robust manner.
Keywords: Ionospheric nowcasting, precision applications