Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

Machine learning-based detection of TEC signatures related to earthquakes and tsunamis: the 2015 Illapel case study

Federica Fuso, Laura Crocetti, Michela Ravanelli and Benedikt Soja
GPS Solutions 28 (3) (2024)
https://doi.org/10.1007/s10291-024-01649-z

Bi-LSTM based vertical total electron content prediction at low-latitude equatorial ionization anomaly region of South India

Veera Kumar Maheswaran, James A. Baskaradas, Raju Nagarajan, Rajesh Anbazhagan, Sriram Subramanian, Venkata Ratnam Devanaboyina and Rupesh M. Das
Advances in Space Research 73 (7) 3782 (2024)
https://doi.org/10.1016/j.asr.2023.08.054

Seismo-ionospheric precursory detection using hybrid Bayesian-LSTM network model with uncertainty-boundaries and anomaly-intensity

Mohd Saqib, Erman Şentürk, Muhammad Arqim Adil and Mohamed Freeshah
Advances in Space Research 74 (4) 1828 (2024)
https://doi.org/10.1016/j.asr.2024.05.023

Physics-informed loss functions for vertical total electron content forecast

Eric Nana Asamoah, Massimo Cafaro, Italo Epicoco, Giorgiana De Franceschi and Claudio Cesaroni
Earth Science Informatics 17 (3) 2569 (2024)
https://doi.org/10.1007/s12145-024-01294-7

Heliophysics and space weather information architecture and innovative solutions: Current status and ways forward

Arnaud Masson, Shing F. Fung, Enrico Camporeale, Masha M. Kuznetsova, Stefaan Poedts, Julie Barnum, Rebecca Ringuette, D. De Zeeuw, Shawn Polson, Viacheslav M. Sadykov, Vicente Navarro, Brian Thomas, Ronald M. Caplan, Jon Linker, Lutz Rastaetter, Chiu Wiegand, Ryan M. McGranaghan, Maksym Petrenko, Chinwe Didigu, Jan Reerink, Jack Ireland and Baptiste Cecconi
Advances in Space Research (2024)
https://doi.org/10.1016/j.asr.2024.05.052

A Cloud-native Approach for Processing of Crowdsourced GNSS Observations and Machine Learning at Scale: A Case Study from the CAMALIOT Project

Grzegorz Kłopotek, Yuanxin Pan, Tobias Sturn, Rudi Weinacker, Linda See, Laura Crocetti, Mudathir Awadaljeed, Markus Rothacher, Ian McCallum, Steffen Fritz, Vicente Navarro and Benedikt Soja
Advances in Space Research 74 (6) 2752 (2024)
https://doi.org/10.1016/j.asr.2024.02.055

Deep Learning‐Based Regional Ionospheric Total Electron Content Prediction—Long Short‐Term Memory (LSTM) and Convolutional LSTM Approach

Se‐Heon Jeong, Woo Kyoung Lee, Hyosub Kil, Soojeong Jang, Jeong‐Heon Kim and Young‐Sil Kwak
Space Weather 22 (1) (2024)
https://doi.org/10.1029/2023SW003763

A stacked machine learning model for the vertical total electron content forecasting

Eric Nana Asamoah, Massimo Cafaro, Italo Epicoco, Giorgiana De Franceschi and Claudio Cesaroni
Advances in Space Research 74 (1) 223 (2024)
https://doi.org/10.1016/j.asr.2024.04.055

MaxEnt SeismoSense Model: Ionospheric Earthquake Anomaly Detection Based on the Maximum Entropy Principle

Linyue Wang, Zhitao Li, Yifang Chen, Jianjun Wang and Jihua Fu
Atmosphere 15 (4) 419 (2024)
https://doi.org/10.3390/atmos15040419

Space weather impact on radio communication and navigation

Mamoru Ishii, Jens Berdermann, Biagio Forte, Mike Hapgood, Mario M. Bisi and Vincenzo Romano
Advances in Space Research (2024)
https://doi.org/10.1016/j.asr.2024.01.043

Prediction of ionospheric total electron content data using spatio-temporal residual network

Nayana Shenvi, E. Chandrasekhar, Anurag Kumar and Hassanali Virani
Advances in Space Research 72 (11) 4856 (2023)
https://doi.org/10.1016/j.asr.2023.09.006

Improving IRI-2016 global total electron content maps using ELM neural network

Masoud Dehvari, Sedigheh Karimi, Saeed Farzaneh and Mohammad Ali Sharifi
Advances in Space Research 72 (9) 3903 (2023)
https://doi.org/10.1016/j.asr.2023.07.022

Estimation of dusk time F-region electron density vertical profiles using LSTM neural networks: A preliminary investigation

Lucas Alves Salles, Paulo Renato Pereira Silva, Guilherme Schwinn Fagundes, Jonas Sousasantos and Alison Moraes
Artificial Intelligence in Geosciences 4 209 (2023)
https://doi.org/10.1016/j.aiig.2023.12.001

Modeling TEC Maps Over China Using Particle Swarm Optimization Neural Networks and Long‐Term Ground‐Based GPS, COSMIC, and Fengyun Data

Shuangshuang Shi, Kefei Zhang, Jiaqi Shi, Andong Hu, Dongsheng Zhao, Zhongchao Shi, Peng Sun, Huajing Wu and Suqin Wu
Space Weather 21 (4) (2023)
https://doi.org/10.1029/2022SW003357

Synthesis‐Style Auto‐Correlation‐Based Transformer: A Learner on Ionospheric TEC Series Forecasting

Yuhuan Yuan, Guozhen Xia, Xinmiao Zhang and Chen Zhou
Space Weather 21 (10) (2023)
https://doi.org/10.1029/2023SW003472

Performance of short-terms prediction methods of vertical total electron content using nonlinear autoregressive neuronal network and stochastic autoregressive model

M. Paula Natali and Amalia Meza
Advances in Space Research 72 (9) 3919 (2023)
https://doi.org/10.1016/j.asr.2023.07.035

Advances in Geospatial Technology in Mining and Earth Sciences

Nhung Le, Benjamin Männel, Luyen K. Bui, et al.
Environmental Science and Engineering, Advances in Geospatial Technology in Mining and Earth Sciences 137 (2023)
https://doi.org/10.1007/978-3-031-20463-0_9

Regional modeling and forecasting of precipitable water vapor using least square support vector regression

Seyyed Reza Ghaffari-Razin, Reza Davari Majd and Navid Hooshangi
Advances in Space Research 71 (11) 4725 (2023)
https://doi.org/10.1016/j.asr.2023.01.030

Ionospheric Electron Density Model by Electron Density Grid Deep Neural Network (EDG-DNN)

Zhou Chen, Bokun An, Wenti Liao, et al.
Atmosphere 14 (5) 810 (2023)
https://doi.org/10.3390/atmos14050810

Ionosphere variability II: Advances in theory and modeling

Ioanna Tsagouri, David R. Themens, Anna Belehaki, Ja-Soon Shim, Mainul M. Hoque, Grzegorz Nykiel, Claudia Borries, Anna Morozova, Teresa Barata and Wojciech J. Miloch
Advances in Space Research (2023)
https://doi.org/10.1016/j.asr.2023.07.056

Ionospheric Weather at Two Starlink Launches during Two-Phase Geomagnetic Storms

Tamara Gulyaeva, Manuel Hernández-Pajares and Iwona Stanislawska
Sensors 23 (15) 7005 (2023)
https://doi.org/10.3390/s23157005

Collecting volunteered geographic information from the Global Navigation Satellite System (GNSS): experiences from the CAMALIOT project

Linda See, Benedikt Soja, Grzegorz Kłopotek, Tobias Sturn, Rudi Weinacker, Santosh Karanam, Ivelina Georgieva, Yuanxin Pan, Laura Crocetti, Markus Rothacher, Vicente Navarro, Steffen Fritz and Ian McCallum
International Journal of Digital Earth 16 (1) 2818 (2023)
https://doi.org/10.1080/17538947.2023.2239761

CARMEN 2 and 3 LEO Electron Flux Measurements Linear Projection Onto RBSP Elliptical Orbit

François Ginisty, Frédéric Wrobel, Robert Ecoffet, Denis Standarovski, Julien Mekki, Marine Ruffenach, Nicolas Balcon and Alain Michez
IEEE Transactions on Nuclear Science 70 (8) 1564 (2023)
https://doi.org/10.1109/TNS.2023.3260904

Forecast Global Ionospheric TEC: Apply Modified U‐Net on VISTA TEC Data Set

Zihan Wang, Shasha Zou, Hu Sun and Yang Chen
Space Weather 21 (8) (2023)
https://doi.org/10.1029/2023SW003494

Ionospheric Total Electron Content Forecasting at a Low-Latitude Indian Location Using a Bi-Long Short-Term Memory Deep Learning Approach

Ram Kumar Vankadara, Mefe Mosses, Md Irfanul Haque Siddiqui, Kutubuddin Ansari and Sampad Kumar Panda
IEEE Transactions on Plasma Science 51 (11) 3373 (2023)
https://doi.org/10.1109/TPS.2023.3325457

Comparison of the Forecast Accuracy of Total Electron Content for Bidirectional and Temporal Convolutional Neural Networks in European Region

Artem Kharakhashyan and Olga Maltseva
Remote Sensing 15 (12) 3069 (2023)
https://doi.org/10.3390/rs15123069

An improved NeQuick-G global ionospheric TEC model with a machine learning approach

K. Sivakrishna, D. Venkata Ratnam and Gampala Sivavaraprasad
GPS Solutions 27 (2) (2023)
https://doi.org/10.1007/s10291-023-01426-4

A Novel Approach for Establishing the Global Ionospheric Model With High Spatiotemporal Resolution

Peng Chen, Yuchen Zhang, Rong Wang, Zhiyuan An and Yibin Yao
IEEE Transactions on Geoscience and Remote Sensing 61 1 (2023)
https://doi.org/10.1109/TGRS.2023.3238044

Aeronomic and Dynamic Correction of the Global Model GTEC for Disturbed Conditions

V. N. Shubin, T. L. Gulyaeva and M. G. Deminov
Геомагнетизм и аэрономия 63 (1) 80 (2023)
https://doi.org/10.31857/S0016794022600491

Using Deep Learning to Map Ionospheric Total Electron Content over Brazil

Andre Silva, Alison Moraes, Jonas Sousasantos, Marcos Maximo, Bruno Vani and Clodoaldo Faria
Remote Sensing 15 (2) 412 (2023)
https://doi.org/10.3390/rs15020412

Aeronomic and Dynamic Correction of the Global Model GTEC for Disturbed Conditions

V. N. Shubin, T. L. Gulyaeva and M. G. Deminov
Geomagnetism and Aeronomy 62 (S1) S74 (2022)
https://doi.org/10.1134/S0016793222600667

Generation of Proxy GIM‐TEC for Extreme Storms Before the Era of GNSS Observations

Tamara Gulyaeva, Valentin Shubin, Haris Haralambous, Manuel Hernández‐Pajares and Iwona Stanislawska
Journal of Geophysical Research: Space Physics 127 (1) (2022)
https://doi.org/10.1029/2021JA029846

An Investigation of Ionospheric TEC Prediction Maps Over China Using Bidirectional Long Short‐Term Memory Method

Shuangshuang Shi, Kefei Zhang, Suqin Wu, Jiaqi Shi, Andong Hu, Huajing Wu and Yu Li
Space Weather 20 (6) (2022)
https://doi.org/10.1029/2022SW003103

The Variation Characteristics and Prediction Performance of TEC in the Geomagnetic Latitude and Local Time Coordinate

Simin Zhang, Xiaocheng Wu and Xiong Hu
Radio Science 57 (12) (2022)
https://doi.org/10.1029/2022RS007544

Modeling of precipitable water vapor from GPS observations using machine learning and tomography methods

Mir-Reza Ghaffari Razin and Behzad Voosoghi
Advances in Space Research 69 (7) 2671 (2022)
https://doi.org/10.1016/j.asr.2022.01.003

Potential Impact of GNSS Positioning Errors on the Satellite‐Navigation‐Based Air Traffic Management

Dabin Xue, Jian Yang and Zhizhao Liu
Space Weather 20 (7) (2022)
https://doi.org/10.1029/2022SW003144

Ionospheric TEC Forecasting over an Indian Low Latitude Location Using Long Short-Term Memory (LSTM) Deep Learning Network

Kanaka Durga Reddybattula, Likhita Sai Nelapudi, Mefe Moses, Venkata Ratnam Devanaboyina, Masood Ashraf Ali, Punyawi Jamjareegulgarn and Sampad Kumar Panda
Universe 8 (11) 562 (2022)
https://doi.org/10.3390/universe8110562

Machine Learning Methods Applied to the Global Modeling of Event-Driven Pitch Angle Diffusion Coefficients During High Speed Streams

G. Kluth , J.-F. Ripoll , S. Has , et al.
Frontiers in Physics 10 (2022)
https://doi.org/10.3389/fphy.2022.786639

Ensemble Machine Learning of Random Forest, AdaBoost and XGBoost for Vertical Total Electron Content Forecasting

Randa Natras, Benedikt Soja and Michael Schmidt
Remote Sensing 14 (15) 3547 (2022)
https://doi.org/10.3390/rs14153547

Convolutional Neural Networks for Automated ULF Wave Classification in Swarm Time Series

Alexandra Antonopoulou, Georgios Balasis, Constantinos Papadimitriou, Adamantia Zoe Boutsi, Athanasios Rontogiannis, Konstantinos Koutroumbas, Ioannis A. Daglis and Omiros Giannakis
Atmosphere 13 (9) 1488 (2022)
https://doi.org/10.3390/atmos13091488

Support Vector Regression model to predict TEC for GNSS signals

Kondaveeti Sivakrishna, Devanaboyina Venkata Ratnam and Gampala Sivavaraprasad
Acta Geophysica 70 (6) 2827 (2022)
https://doi.org/10.1007/s11600-022-00954-w

Optimal Transformer Modeling by Space Embedding for Ionospheric Total Electron Content Prediction

Mengying Lin, Xuefen Zhu, Gangyi Tu and Xiyaun Chen
IEEE Transactions on Instrumentation and Measurement 71 1 (2022)
https://doi.org/10.1109/TIM.2022.3211550

A novel hybrid Machine learning model to forecast ionospheric TEC over Low-latitude GNSS stations

G. Sivavaraprasad, I. Lakshmi Mallika, K. Sivakrishna and D. Venkata Ratnam
Advances in Space Research 69 (3) 1366 (2022)
https://doi.org/10.1016/j.asr.2021.11.033

ED‐ConvLSTM: A Novel Global Ionospheric Total Electron Content Medium‐Term Forecast Model

Guozhen Xia, Fubin Zhang, Cheng Wang and Chen Zhou
Space Weather 20 (8) (2022)
https://doi.org/10.1029/2021SW002959

Modeling and forecasting of ionosphere TEC using least squares SVM in central Europe

Seyyed Reza Ghaffari-Razin, Amir Reza Moradi and Navid Hooshangi
Advances in Space Research 70 (7) 2035 (2022)
https://doi.org/10.1016/j.asr.2022.06.020

Space Weather Services for Civil Aviation—Challenges and Solutions

Kirsti Kauristie, Jesse Andries, Peter Beck, Jens Berdermann, David Berghmans, Claudio Cesaroni, Erwin De Donder, Judith de Patoul, Mark Dierckxsens, Eelco Doornbos, Mark Gibbs, Krista Hammond, Haris Haralambous, Ari-Matti Harri, Edmund Henley, Martin Kriegel, Tiera Laitinen, Marcin Latocha, Yana Maneva, Loredana Perrone, Emanuele Pica, Luciano Rodriguez, Vincenzo Romano, Dario Sabbagh, Luca Spogli, et al.
Remote Sensing 13 (18) 3685 (2021)
https://doi.org/10.3390/rs13183685

One‐Day Forecasting of Global TEC Using a Novel Deep Learning Model

Sujin Lee, Eun‐Young Ji, Yong‐Jae Moon and Eunsu Park
Space Weather 19 (1) (2021)
https://doi.org/10.1029/2020SW002600

Prediction of Ionospheric TEC Based on the NARX Neural Network

Liu Guoyan, Gao Wang, Zhang Zhengxie, Zhao Qing and Chao Hu
Mathematical Problems in Engineering 2021 1 (2021)
https://doi.org/10.1155/2021/7188771

A Neural Network-Based TEC Model Capable of Reproducing Nighttime Winter Anomaly

Marjolijn Adolfs and Mohammed Mainul Hoque
Remote Sensing 13 (22) 4559 (2021)
https://doi.org/10.3390/rs13224559

Predicting the Effects of Solar Storms on the Ionosphere Based on a Comparison of Real-Time Solar Wind Data with the Best-Fitting Historical Storm Event

Erik Schmölter and Jens Berdermann
Atmosphere 12 (12) 1684 (2021)
https://doi.org/10.3390/atmos12121684

GIMLi: Global Ionospheric total electron content model based on machine learning

Aleksei V. Zhukov, Yury V. Yasyukevich and Aleksei E. Bykov
GPS Solutions 25 (1) (2021)
https://doi.org/10.1007/s10291-020-01055-1

Space Weather research in the Digital Age and across the full data lifecycle: Introduction to the Topical Issue

Ryan M. McGranaghan, Enrico Camporeale, Manolis Georgoulis and Anastasios Anastasiadis
Journal of Space Weather and Space Climate 11 50 (2021)
https://doi.org/10.1051/swsc/2021037

Prediction of TEC using NavIC/GPS data with geostatistical method/forecasting capability comparison with other models

R. Mukesh, V. Karthikeyan, P. Soma and P. Sindhu
Astrophysics and Space Science 365 (9) (2020)
https://doi.org/10.1007/s10509-020-03868-5