Equatorial Plasma Bubble Detection using the Convolutional Neural Network (CNN) and Support Vector Machine (SVM)

Thanakulketsarat, Thananphat; Supnithi, Pornchai; Myint, Lin Min Min; Hozumi, Kornyanat

doi:10.23919/URSIGASS57860.2023.10265497

Equatorial Plasma Bubble Detection using the Convolutional Neural Network (CNN) and Support Vector Machine (SVM)

Author(s)

Thanakulketsarat, Thananphat

Supnithi, Pornchai

Myint, Lin Min Min

Hozumi, Kornyanat

Date Issued

January 1, 2023

Type

Conference Paper

DOI

10.23919/URSIGASS57860.2023.10265497

Abstract

Equatorial plasma bubbles (EPB) refer to the area of low electron density in the Earth's ionosphere near the equator during post sunset and post-midnight. They influence the radio communications and GPS signals. In this work, we study the EPB occurrences and characteristics using the VHF radar images observed at the Chumphon station, Thailand, near the magnetic equator.. We develop an EPB image detection system using a hybrid learning technique with convolutional neural network (CNN) and support vector machine (SVM) and evaluate the accuracy of the proposed CNN-SVM model using two kernels: polynomial kernel and radial basis function (RBF) kernel.

Citation

2023 35th General Assembly and Scientific Symposium of the International Union of Radio Science Ursi Gass 2023, 2023