Oct 3, 2019 � In this paper, we focus on predicting the phase fluctuations of GNSS radio waves, known as phase scintillations. We propose a novel architecture�...
In this paper, we focus on predicting the phase fluctuations of GNSS radio waves, known as phase scin- tillations. We propose a novel architecture and loss�...
Oct 3, 2019 � In this paper, we focus on predicting the phase fluctuations of GNSS radio waves, known as phase scin- tillations. We propose a novel�...
Oct 3, 2019 � In this paper, we focus on predicting the phase fluctuations of GNSS radio waves, known as phase scintillations. We propose a novel architecture�...
Prediction of GNSS Phase Scintillations: A Machine Learning Approach. Lamb K ... Machine Learning and Artificial Intelligence. DOI. 10.48550/arxiv�...
Dec 14, 2023 � This paper presents a neural network approach to predict ionospheric scintillation using datasets obtained from distributed geodetic receivers�...
In this work, we developed two machine learning models for the prediction of ionospheric scintillation events at the equatorial anomaly during the maximum and�...
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The present contribution uses scintillation time series estimates and proposes a bivariate times series classification of the scintillation signal.
The results showed that the durability of the LACNN model over the span of a year can predict irregularities up to 3 hours in advance with an accuracy of�...
Oct 10, 2021 � This study presents an image-based convolutional long short-term memory (convLSTM) machine learning algorithm to predict storm-time ionospheric irregularities.