1 / 11

Integration of METU-IFS Server to COST 724 Server (BIRA)

COST 724 MCM, Antalya, Turkey, 27-30 March 2006. Integration of METU-IFS Server to COST 724 Server (BIRA). E. Tulunay 1,2 , D. Heynderickx 3 , E.T. Senalp 1 , M. Özdemirci 1 , Y.I. Özkok 1 , Y. Tulunay 4 (1) METU , Dept. of Electrical and Electronics Eng., Ankara, Turkey

uyen
Télécharger la présentation

Integration of METU-IFS Server to COST 724 Server (BIRA)

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. COST 724 MCM, Antalya, Turkey, 27-30 March 2006 Integration of METU-IFS Server to COST 724 Server (BIRA) E. Tulunay1,2, D. Heynderickx3, E.T. Senalp1, M. Özdemirci1, Y.I. Özkok1, Y. Tulunay4 (1) METU, Dept. of Electrical and Electronics Eng., Ankara, Turkey (2) TUBITAK, MRC, Information Technologies Institute, Gebze, Kocaeli, Turkey (3) BIRA, Brussel, Belgium (4) METU, Dept. of Aerospace Eng., Ankara, Turkey COST 724 MCM, Antalya, Turkey

  2. CONTENTS • Objective • METU-NN Model • METU-IFS Server and Client • METU-IFS comm. with COST 724 Server • Conclusion • Acknowledgement • References COST 724 MCM, Antalya, Turkey

  3. OBJECTIVE • Since 1990, we have capacity to forecast ionospheric parameters • We will make NN available to ERA through COST 724 activities conducted by D. Heynderickx COST 724 MCM, Antalya, Turkey

  4. 2. METU-NN (Middle East Technical University Neural Networks models) Modeling of nonlinear problems by using NN NNs: flexible, data-driven; to be used along with analytical models METU-NN: - forecasting of system parameters including the NES processes, METU-NN-C: - identification of systems by Cascade Models [Tulunay Y. et al., (2004-a; b);(2005-a); Senalp et al., (2005)] COST 724 MCM, Antalya, Turkey

  5. COST 724 MCM, Antalya, Turkey

  6. 3. METU-IFS (METU Ionospheric Forecasting Software) • -2003-2005: Web based METU-IFS [Ozkok Y.I., 2005] • - 2005 – present: Providing a mean so that METU-IFS and BIRA comm. with each other • Selected model:“The METU-NN SolarRadio Flux”[Tulunay Y. et al., 2005-b] COST 724 MCM, Antalya, Turkey

  7. Specifications: • - Input (12): temporal data; SXR data • one hidden layer with 50 neurons • Output (1):forecast of occurrences of large X-ray Events one month in advance COST 724 MCM, Antalya, Turkey

  8. FTP FTP METU-IFS Server (METU-NN) BIRA – COST 724 Server PC PC(METU-IFS Client) Serialized TCP/IP Comm. 4.METU-IFS comm. with COST 724 Server COST 724 MCM, Antalya, Turkey

  9. 5. Conclusion METU-IFS and COST 724 Servers – to be integrated for the use of European Research Area COST 724 MCM, Antalya, Turkey

  10. 6.Acknowledgement • Thanks to • COST 724 • TÜBİTAK MAM • TÜBİTAK ÇAYDAG COST 724 MCM, Antalya, Turkey

  11. 7. References -Tulunay Y., Tulunay E., Senalp E.T., The Neural Network Technique-1: A General Exposition, Adv. SpaceRes., Vol. 33, No. 6, pp. 983-987, 2004-a. -Tulunay Y., Tulunay E., Senalp E.T., The Neural Network Technique-2: An Ionospheric Example Illustrating its Application, Adv. Space Res., Vol. 33, No. 6, pp. 988-992, 2004-b. -Ozkok Y.I., Web Based Ionospheric Forecasting using Neural Network and Neurofuzzy Methods, MSc. Thesis, Middle East Technical University, Department of Electrical and Electronics Engineering, Ankara, Turkey, April 2005. -Senalp E.T., Tulunay E., Tulunay Y., Neural Networks and Cascade Modeling Technique in System Identification, 14th Turkish Symposium on Artificial Intelligence and Neural Networks, TAINN 2005, pp.286-293, 16-17 June 2005, Cesme, Izmir, Turkey. -Tulunay Y., Sibeck D.G., Senalp E.T., Tulunay E., Forecasting magnetopause crossing locations by usingNeural Networks, Adv. Space Res., Vol 36, No.12, pp. 2378-2383, 2005-a. - Tulunay Y., Messerotti M., Senalp E.T., Tulunay E., Molinaro M., Ozkok Y.I., Yapici T., Altuntas E., Cavus N., Neural Network Modeling in Forecasting the Near Earth Space Parameters: Forecasting of the Solar Radio Fluxes, COST 724: "Developing the scientific basis for monitoring, modeling and predicting Space Weather" Scientific Workshop, Proceedings CD, 10-14 October 2005, Athens, Greece, 2005-b. COST 724 MCM, Antalya, Turkey

More Related