An experiment of predicting Total Electron Content (TEC) by fuzzy inference systems

被引：0
|
作者：
O. Akyilmaz
N. Arslan
机构：
[1] Istanbul Technical University,Department of Geodesy and Photogrammetry Engineering
[2] Yildiz Technical University,Department of Geodesy and Photogrammetry Engineering
来源：
Earth, Planets and Space | 2008年 / 60卷
关键词：
GPS; ionosphere; VTEC; prediction;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The Total Electron Content (TEC) is predicted by fuzzy inference systems for various station-satellite pairs. GPS data from the GRAZ, HFLK, LINZ, MOPI and UZHL permanent stations are processed in order to obtain the vertical total electron content (VTEC) using differenced carrier-smoothed code observations. The quality of the VTEC prediction was studied on 9 and 11 September 2005 (DOY 252 and 254). The predictions were computed for 5, 10 and 15 min intervals. The mean accuracies of predictions are about 0.1, 0.2 and 0.3 TECU for these time intervals. More than 98% of the VTEC is successfully recovered with the proposed prediction method.
引用
收藏
页码：967 / 972
页数：5
相关论文
共 50 条
  • [31] Ionospheric earthquake effects detection based on Total Electron Content (TEC) GPS Correlation
    Sunardi, Bambang
    Muslim, Buldan
    Sakya, Andi Eka
    Rohadi, Supriyanto
    Sulastri
    Murjaya, Jaya
    41ST HAGI ANNUAL CONVENTION AND EXHIBITION 2016, 2018, 132
  • [32] Revisit the calibration errors on experimental slant total electron content (TEC) determined with GPS
    Nie, Wenfeng
    Xu, Tianhe
    Rovira-Garcia, Adria
    Juan Zornoza, Jose Miguel
    Sanz Subirana, Jaume
    Gonzalez-Casado, Guillermo
    Chen, Wu
    Xu, Guochang
    GPS SOLUTIONS, 2018, 22 (03)
  • [33] Comparison of adaptive neuro-fuzzy inference system and recurrent neural network in vertical total electron content forecasting
    Perez Bello, Dinibel
    Natali, Maria P.
    Meza, Amalia
    NEURAL COMPUTING & APPLICATIONS, 2019, 31 (12): : 8411 - 8422
  • [34] Comparison of adaptive neuro-fuzzy inference system and recurrent neural network in vertical total electron content forecasting
    Dinibel Pérez Bello
    María P. Natali
    Amalia Meza
    Neural Computing and Applications, 2019, 31 : 8411 - 8422
  • [35] GPS Vertical Total Electron Content (TEC) Dual Frequency Technique and TEC Map at Ionosphere Layer Using Malaysian Data
    Ya'acob, Norsuzila
    Abdullah, Mardina
    Ismail, Mahamod
    INTERNATIONAL CONFERENCE ON FUTURE COMPUTER AND COMMUNICATIONS, PROCEEDINGS, 2009, : 589 - 593
  • [36] Prediction of Global Ionospheric Total Electron Content (TEC) Based on SAM-ConvLSTM Model
    Luo, Hanze
    Gong, Yingkui
    Chen, Si
    Yu, Cheng
    Yang, Guang
    Yu, Fengzheng
    Hu, Ziyue
    Tian, Xiangwei
    SPACE WEATHER-THE INTERNATIONAL JOURNAL OF RESEARCH AND APPLICATIONS, 2023, 21 (12):
  • [37] Total Electron Content (TEC) Estimation Using GPS Measurements Onboard TerraSAR-X
    Choi, Key-Rok
    Lightsey, E. Glenn
    PROCEEDINGS OF THE 2008 NATIONAL TECHNICAL MEETING OF THE INSTITUTE OF NAVIGATION - NTM 2008, 2008, : 923 - 934
  • [38] Initial prediction of Total Electron Content (TEC) at a low latitude station using neural network
    Homam, M.J.
    2014 IEEE Asia-Pacific Conference on Applied Electromagnetics, APACE 2014 - Proceeding, 2015, : 111 - 114
  • [39] Initial Prediction of Total Electron Content (TEC) At a Low Latitude Station Using Neural Network
    Homam, M. J.
    2014 IEEE ASIA-PACIFIC CONFERENCE ON APPLIED ELECTROMAGNETICS (APACE), 2014,
  • [40] Changes in total electron content (TEC) during the annular solar eclipse of 15 January 2010
    Kumar, Sanjay
    Singh, A. K.
    ADVANCES IN SPACE RESEARCH, 2012, 49 (01) : 75 - 82
12345