DAYTIME AND NIGHTTIME VLF SIGNAL CLASSIFICATION UTILIZING MACHINE LEARNING METHODS
Filip Arnaut.
Publication
BOOK OF ABSTRACTS AND CONTRIBUTED PAPERS - International scientific conference: Meeting on new trends in Astronomy & Earth Observation, Page 15-20, https://doi.org/10.69646/aob241203
BOOK OF ABSTRACTS AND CONTRIBUTED PAPERS - International scientific conference: Meeting on new trends in Astronomy & Earth Observation, November 25-29, 2024, Belgrade, Serbia, Edited by Vladimir A. Srećković, Aleksandra Kolarski, Milica Langović, Filip Arnaut and Nikola Veselinović
Published by: Scientific Society Isaac Newton Belgrade
Published: 15. 12. 2024.
Abstract
Abstract:  The  automatic  classification  of  ionospheric  very low frequency  (VLF)  signals  is  a  current  research  endeavor aimed  at creating  a  machine-learning  (ML)  methodology capable  of differentiating  among  various  influences  on  VLF signals,  including  solar  flares,  VLF  receiver  malfunctions, nighttime  VLF  signals,  and other factors. This communication discusses the enhancement in ML classification  of  daytime  and nighttime  ionospheric  VLF  signals,  including  the  different methodologies,  data  processing,  and  various  processes  that demonstrated improvement over prior research. - FULL TEXT available in PDF.
 
                        
                             
                        
                            
 PDF
 PDF
