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

dc.contributor.authorThananphat Thanakulketsarat
dc.contributor.authorPornchai Supnithi
dc.contributor.authorLin Min Min Myint
dc.contributor.authorKornyanat Hozumi
dc.date.accessioned2026-05-08T19:23:35Z
dc.date.issued2023-8-19
dc.description.abstractEquatorial 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.
dc.identifier.doi10.23919/ursigass57860.2023.10265497
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/19133
dc.subjectCurrency Recognition and Detection
dc.subjectFault Detection and Control Systems
dc.subjectAnomaly Detection Techniques and Applications
dc.titleEquatorial Plasma Bubble Detection using the Convolutional Neural Network (CNN) and Support Vector Machine (SVM)
dc.typeArticle

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