A complete understanding of the causes of Sporadic-E propagation has so far defied analysis. The large number of possible parameters, many of which are non-linear and/or stochastic (random) in nature, has made it very difficult to model the system well enough to tease apart the causes and effects so as to be able to predict this phenomenon. This research effort, spurred in part by Joe Dzekovich’s (K1YOW) QST article which suggested a possible relationship between Upper Level Lows and Sporadic E on 6 meters, is applying methods of Deep Learning (a branch of Artificial Intelligence) combined with traditional analytics to better understand what make the 6-meter “magic” band work. The HamSCI HARC spots database is used along with data from NOAA, NASA, and meteorite monitoring networks. This is a progress briefing on research which is ongoing and not yet complete.
BT - HamSCI Workshop 2019 C1 -20190322_1130-Bill_Engelke_AB4EJ.pdf
CY - Cleveland, OH DA - 03/2019 LA - eng N2 -A complete understanding of the causes of Sporadic-E propagation has so far defied analysis. The large number of possible parameters, many of which are non-linear and/or stochastic (random) in nature, has made it very difficult to model the system well enough to tease apart the causes and effects so as to be able to predict this phenomenon. This research effort, spurred in part by Joe Dzekovich’s (K1YOW) QST article which suggested a possible relationship between Upper Level Lows and Sporadic E on 6 meters, is applying methods of Deep Learning (a branch of Artificial Intelligence) combined with traditional analytics to better understand what make the 6-meter “magic” band work. The HamSCI HARC spots database is used along with data from NOAA, NASA, and meteorite monitoring networks. This is a progress briefing on research which is ongoing and not yet complete.
PB - HamSCI PP - Cleveland, OH PY - 2019 T2 - HamSCI Workshop 2019 TI - New Directions in Sporadic-E Research ER -