15 may 2006ictp, space weather - metu-nn1 ictp-cost-usnswp-cawses-inaf-infn international advanced...
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15 May 2006 ICTP, Space Weather - METU-NN 1
ICTP-COST-USNSWP-CAWSES-INAF-INFN International Advanced School on Space Weather2-19 May 2006, Trieste, Italy
FORECASTING TOTAL ELECTRON CONTENT (TEC) FOR CONSTRUCTING MAPS ESPECIALLY DURING HIGH SOLAR ACTIVITY PERIODS
Erdem Turker Senalp(1), Ersin Tulunay(1), Sandro Maria Radicella(2), Yurdanur Tulunay(3)
(1)Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey, [email protected], [email protected]
(2)Aeronomy and Radiopropagation Laboratory, Abdus Salam International Centre for Theoretical Physics, Trieste, Italy, [email protected]
(3)Department of Aerospace Engineering, Middle East Technical University, Ankara, Turkey, [email protected]
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Contents
- Biological to Artificial Neurons
- Middle East Technical University Neural Network model (METU NN)
- METU NN Forecasting TEC Maps
- Results
- Conclusions
- References
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Biological to Artificial Neurons
Tulunay, 2004
Halici, 2006 Halici, 2006
METU-NN
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Middle East Technical University Neural Network model (METU NN)
METU NN Forecasting TEC Maps [1]
- power of forecasting non-linear process parameters
- forecast TEC values and the maps [1]
- Observed GPS TEC data [Ciraolo, 2004] :- Ten minute vertical TEC databetween 1 Nov. 2003 and 11 Dec. 2003- 104 grid locations centered over Italybetween latitudes of (35.5º N; 47.5º N) and
longitudes of (5.5º E; 19.5º E)
[1] Tulunay E., Senalp E.T., Radicella S.M., Tulunay Y., Forecasting TEC Maps by Neural Network Technique, Radio Science, submitted in 2005, (2006).
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METU NN technique
- to forecast TEC grid values
- surfaces in mapping the forecast grid values
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- Figure 1. Observed (dotted) and 1 hour ahead forecast (solid) TEC during 16 Nov. 2003 03:10 UT - 29 Nov. 2003 24:00 UT for single grid point
(13.5˚ E; 41.5˚ N)
Results
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- Figure 2. Scatter Diagram (dots) with best-fit line (solid) for the 1 hour ahead Forecast mapping and Observed TEC values for single grid point (13.5˚ E; 41.5˚ N) for 20 November 2003
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METU NN technique
- to forecast TEC grid values
- surfaces in mapping the forecast grid values
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- Video 1. Observed and 1 hour ahead forecast TEC Maps by METU-NN during the afternoon of 20 Nov. 2003
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- Figure 3. Absolute Error Map of observed and 1 hour ahead forecast TEC during 16-29 Nov. 2003
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Location 11.5˚E38.5˚N
13.5˚E41.5˚N
15.5˚E44.5˚N
OverallTEC Map
Root Mean Square Error (TECU)
2.1556 2.0501 2.1444 2.2969
Absolute Error (TECU) 1.5785 1.4846 1.5168 1.6537
Normalized Error 0.1429 0.1522 0.1630 0.1563
Cross Correlation Coefficient 0.9775 0.9746 0.9696 0.9699
Table 1. Error Table for 1 h in advance forecasts by METU-NN for the validation time period (16-29 Nov. 2003)
The forecast mapping error values - within operational tolerance[Radicella, 2004].
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Conclusions
- The system reached correct operating point during training
- METUNN learned the inherent nonlinearities of the process
- Representable data in inputs
+
Proper construction of METUNN
=
complex nonlinear processes are modelled
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References
Tulunay E., Senalp E.T., Radicella S.M., Tulunay Y. (2006), Forecasting TEC Maps by Neural Network Technique, Radio Science, (submitted in 2005).
Ciraolo, G. (2004), Private communication.
Radicella S.M. (2004), Private communication.
Tulunay, E. (1991), Introduction to Neural Networks and their Application to Process Control, in Neural Networks Advances and Applications, edited by E. Gelenbe, 241-273, Elsevier Science Publishers B.V., North-Holland.
Tulunay E., E.T. Senalp, Lj.R. Cander, Y.K. Tulunay, A.H. Bilge, E. Mizrahi, S.S. Kouris, N. Jakowski (2004), Development of algorithms and software for forecasting, nowcasting and variability of TEC, Annals of Geophysics, 47(2/3), 1201-1214.
Tulunay Y., E. Tulunay, and E.T. Senalp (2001), An Attempt to Model the Influence of the Trough on HF Communication by Using Neural Network, Radio Science, 36(5), 1027-1041, September - October 2001.
Tulunay Y., E. Tulunay, and E.T. Senalp (2004-a), The Neural Network Technique-1: A General Exposition, Adv. Space Res., 33(6), 983-987.
Tulunay Y., E. Tulunay, and E.T. Senalp (2004-b), The Neural Network Technique-2: An Ionospheric Example Illustrating its Application, Adv. Space Res., 33(6), 988-992.
Halici, U. (2006), Artificial Neural Networks, Lecture Notes, Ch1, METU EEE, Ankara, Turkey, 3, 8. “http://vision1.eee.metu.edu.tr/%7Ehalici/543LectureNotes/lecturenotes-pdf/ch1.pdf”.