Thanakulketsarat, Thananphat

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Thanakulketsarat, Thananphat
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Thanakulketsarat, T.
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thananphat.th@kmitl.ac.th

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    Equatorial Plasma Bubble Detection by Support Vector Machine at Chumphon Station, Thailand
    (2022-01-01)
    Thanakulketsarat, Thananphat
    ;
    Supnithi, Pornchai
    ;
    Myint, Lin Min Min
    ;
    Hozumi, Kornyanat
    Equatorial Plasma Bubble (EPB) is a phenomenon in which depletion of plasma density occurs in the ionosphere particularly in the equatorial region. It can degrade the performances of the navigation system and satellite communication. In this work, we analyze EPB based on the very-high frequency (VHF) radar images at Chumphon station, Thailand. Then an EPB detection system using the support vector machine (SVM) technique is developed, and the accuracies of the systems using different kernels: linear kernel, the polynomial kernel, the radial basic functions kernel (RBF), and the sigmoid kernel are compared. Among the different kernels, we find that the RBF kernel gives the highest accuracy in prediction at 86.67 percent.
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    Ionograms Scaling by Using the Convolutional Neural Network
    (2021-03-10)
    Thanakulketsarat, Thananphat
    ;
    Sopon, Thanomsak
    ;
    Phakphisut, Watid
    ;
    Hozumi, Kornyanat
    ;
    Wongtrairat, Wannaree
    Ionosphere in F layer has the most irregularity for phenomenon occurrence of amplitude scintillation which leads to the problem in the satellite signals. Ionosphere can be observed by Ionosonde to study F2 layer critical frequency (foF2) parameter and height of F layer (h'F) parameter from the ionogram. This paper presents the convolutional neural network (CNN) to determine foF2 and h'F parameters. The simulation start from passing the ionogram images to the proposed CNN model with 2,000 epoch training. The simulated accuracies of both foF2 and h'F parameters are equal to 92.8% and 98.4%, respectively.
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    Equatorial Ionospheric Irregularity Detection and Analysis Using 2-D ROTI Maps and VHF Radar Images During the Upcoming Solar Maximum
    (2026-01-01)
    Supnithi, P.
    ;
    Myint, L. M.M.
    ;
    Tongkasem, N.
    ;
    Thanakulketsarat, T.
    ;
    Nishioka, M.
    In this work, we analyze the ionospheric irregularities at Chumphon station, Thailand, using observational data from GNSS receivers as well as VHF radar and ionosonde at Chumphon station, Thailand. The ionospheric irregularity event on 20 March 2020 and the super solar storms during 8–12 May 2024 are studied. Both instruments show traces the irregularities and interesting daytime fluctuation in total electron content over Thailand area. The statistics of ionospheric irregularities from 2020 to 2024 show that as we enter the solar maximum of the 25<sup>th</sup> solar cycle, more occurrences of ionospheric irregularities are clearly seen.
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    Equatorial Plasma Bubble Detection using the Convolutional Neural Network (CNN) and Support Vector Machine (SVM)
    (2023-01-01)
    Thanakulketsarat, Thananphat
    ;
    Supnithi, Pornchai
    ;
    Myint, Lin Min Min
    ;
    Hozumi, Kornyanat
    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.
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