A classification of meteor radio echoes based on artificial neural network

Abstract

© by Mikhail Danilov, Arkadi Karpov, published by De Gruyter 2018. An artificial neural network is described for classification of meteor trails into the distinct overdense, intermediate and underdense trail categories. The neural network was trained and on model data obtained using the "KAMET" program and tested on real data. The best result of classification success rate of 95% without according to the heights of the formation of meteor trails. Results of classification with according to the heights of the formation of meteor trails are 82% - 91%.