Ensemble machine learning of random forest, AdaBoost and XGBoost for vertical total electron content forecasting
Space weather describes varying conditions between the Sun and Earth that can degrade
Global Navigation Satellite Systems (GNSS) operations. Thus, these effects should be …
Global Navigation Satellite Systems (GNSS) operations. Thus, these effects should be …
Uncertainty Quantification for Machine Learning‐Based Ionosphere and Space Weather Forecasting: Ensemble, Bayesian Neural Network, and Quantile Gradient …
Abstract Machine learning (ML) has been increasingly applied to space weather and
ionosphere problems in recent years, with the goal of improving modeling and forecasting …
ionosphere problems in recent years, with the goal of improving modeling and forecasting …
Ionospheric Error Models for Satellite-Based Navigation—Paving the Road towards LEO-PNT Solutions
Low Earth Orbit (LEO) constellations have recently gained tremendous attention in the
navigational field due to their larger constellation size, faster geometry variations, and higher …
navigational field due to their larger constellation size, faster geometry variations, and higher …
MaxEnt SeismoSense Model: Ionospheric Earthquake Anomaly Detection Based on the Maximum Entropy Principle
L Wang, Z Li, Y Chen, J Wang, J Fu - Atmosphere, 2024 - mdpi.com
In our exploration, we aimed at identifying seismic anomalies using limited ionospheric data
for earthquake forecasting and we meticulously compiled datasets under conditions of …
for earthquake forecasting and we meticulously compiled datasets under conditions of …
Global Ionospheric Modeling Using Multi-GNSS: A Machine Learning Approach
The ionosphere is a significant error source in space-geodetic techniques, such as the
Global Navigation Satellite System (GNSS) and satellite radar altimetry. This is especially …
Global Navigation Satellite System (GNSS) and satellite radar altimetry. This is especially …
Ionospheric TEC prediction using FFNN during five different X Class solar flares of 2021 and 2022 and comparison with COKSM and IRI PLAS 2017
Abstract The Ionospheric Total Electron Content (TEC) measured in the ray path of the
signals directly contributes to the Range Error (RE) of the satellite signals, which affects …
signals directly contributes to the Range Error (RE) of the satellite signals, which affects …
Ionospheric Modeling by Using Self-Organizing Map (SOM) Under the Disturbed Condition
K Murai, Y Sato, S Fujita, Y Tsukamoto… - Proceedings of the 37th …, 2024 - ion.org
Ionospheric delay is the main error source of Global Navigation Satellite Systems (GNSS),
and it is important to estimate an accurate understanding of ionosphere delay conditions …
and it is important to estimate an accurate understanding of ionosphere delay conditions …
Ground Subsystem Error Contribution of a Multi-Constellation GBAS Based on a CORS Network in the Vicinity of Airport Areas
EMA Cuestas, P Supnithi, J Budtho, S Saito - … of the Satellite Division of The …, 2024 - ion.org
The use of multi-constellations in the Ground Based Augmentation Systems (GBAS) brings
new scenarios to the modeling and certification path in comparison to a single constellation …
new scenarios to the modeling and certification path in comparison to a single constellation …
[PDF][PDF] Ionospheric Error Models for Satellite-Based Navigation—Paving the Road towards LEO-PNT Solutions. Computers 2024, 13, 4
Low Earth Orbit (LEO) constellations have ecently gained tremendous attention in the
navigational field due to their arger constellation size, faster geometry variations, and higher …
navigational field due to their arger constellation size, faster geometry variations, and higher …