Haris Haralambous

TL;DR: This paper proposes an extension to conventional regression neural networks for replacing the point predictions they produce with prediction intervals that satisfy a required level of confidence and evaluates the proposed method on four benchmark datasets.

TL;DR: Ionospheric total electron content (TEC) variations prior to two large earthquakes in Nepal (M= 7.8) and Chile (M = 8.3) in 2015 were analyzed using measurements from global navigation satellite system network with the aim to detect possible ionospheric anomalies associated to these seismic events and describe their main features, by applying statistical and spectral analysis as discussed by the authors.

TL;DR: In this paper, the analytical description of the topside ionosphere included in the NeQuick model is studied in detail, where the modeled scale height behavior is analyzed at infinity and for the lowest part of the topology.

TL;DR: The largest geomagnetic storm in solar cycle 24 occurred during March 17-18, 2015 where the main phase of the storm reached the negative minimum at 22:00 UT as discussed by the authors.

TL;DR: The development of Neural Network models to predict the likelihood of interference experienced by Broadcast users in the HF spectrum (3-30 MHz) are presented, based upon several years of measurements recorded at Linkoping (Sweden) across the HF band.