Detecting Total Electron Content Precursors Before Earthquakes by Examining Total Electron Content Images Based on Butterworth Filter in Convolutional Neural Networks

Daily total electron content (TEC) images created by splitting TEC maps for three time periods from September 1 to 24, 1999; from February 1 to 24, 2003; and from May 1 to 24, 2003 (Taiwan Standard Time [TST]) as training images (inputs) were used to create two convolutional neural network (CNN) mod...

Full description

Bibliographic Details
Main Authors: Jyh-Woei Lin, Juing-Shian Chiou
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9113262/
id doaj-11c619cbed2842978d3a3178dc867c31
record_format Article
spelling doaj-11c619cbed2842978d3a3178dc867c312021-03-30T01:50:58ZengIEEEIEEE Access2169-35362020-01-01811047811049410.1109/ACCESS.2020.30013379113262Detecting Total Electron Content Precursors Before Earthquakes by Examining Total Electron Content Images Based on Butterworth Filter in Convolutional Neural NetworksJyh-Woei Lin0Juing-Shian Chiou1https://orcid.org/0000-0001-6875-0172Binjiang College, Nanjing University of Information Science and Technology, Wuxi, ChinaDepartment of Electrical Engineering, Southern Taiwan University of Science and Technology, Tainan, TaiwanDaily total electron content (TEC) images created by splitting TEC maps for three time periods from September 1 to 24, 1999; from February 1 to 24, 2003; and from May 1 to 24, 2003 (Taiwan Standard Time [TST]) as training images (inputs) were used to create two convolutional neural network (CNN) models. However, splitting the TEC maps of the three time periods into daily TEC images caused wedge effects. The wedge effects were reduced using a low-pass filter called the Butterworth filter. This resulted in clearer TEC precursors for earthquakes, facilitating the identification of earthquakes of magnitude M<sub>w</sub> &#x2265; 5.0 that exhibited associated TEC precursors during three periods, particularly for the Chi-Chi earthquake of September21, 1999. The results of this study were compared with those of Lin et al. and Lin associated with the Chi-Chi earthquake. Simultaneously, two CNN models that were developed were verified to be rational due to the high accuracy of their predictions. These two models were used to verify each other's accuracies and to demonstrate the reliability of the method in this study. Therefore, statistical analysis was not the aim. The final outputs of the two CNN model were defined as similarities. Similarities, which are larger than 0.5, were defined as TEC precursors of earthquakes. TEC precursors described as temporal TEC multi-precursors (TTMPs) by Zoran et al. were detectable on the 1st, 3rd, and 4th days (that is, on September 17, 18, and 20, 1999, respectively) prior to the Chi-Chi earthquake of September 21, 1999. These results are consistent with those of Liu et al. and Lin. A TEC precursor on May 13, 2003, (TST) was detectable 2 days prior to the earthquake on May 15, 2003, (TST) with the magnitude (M<sub>w</sub>) of 5.52. The low standard deviation (STD) and mean square error (MSE) confirm the reliability of both CNN models. Regarding mechanical principles, the TTMPs related to the Chi-Chi earthquake were caused by an electric field. The cause of the TEC precursor on May 13, 2003, prior to the earthquake on May 15, 2003, was an argument without any corresponding study for comparison.https://ieeexplore.ieee.org/document/9113262/Daily total electron content (TEC) imagesconvolutional neural network (CNN)wedge effectsButterworth filtertemporal TEC multi-precursors (TTMPs)Chi-Chi earthquake
collection DOAJ
language English
format Article
sources DOAJ
author Jyh-Woei Lin
Juing-Shian Chiou
spellingShingle Jyh-Woei Lin
Juing-Shian Chiou
Detecting Total Electron Content Precursors Before Earthquakes by Examining Total Electron Content Images Based on Butterworth Filter in Convolutional Neural Networks
IEEE Access
Daily total electron content (TEC) images
convolutional neural network (CNN)
wedge effects
Butterworth filter
temporal TEC multi-precursors (TTMPs)
Chi-Chi earthquake
author_facet Jyh-Woei Lin
Juing-Shian Chiou
author_sort Jyh-Woei Lin
title Detecting Total Electron Content Precursors Before Earthquakes by Examining Total Electron Content Images Based on Butterworth Filter in Convolutional Neural Networks
title_short Detecting Total Electron Content Precursors Before Earthquakes by Examining Total Electron Content Images Based on Butterworth Filter in Convolutional Neural Networks
title_full Detecting Total Electron Content Precursors Before Earthquakes by Examining Total Electron Content Images Based on Butterworth Filter in Convolutional Neural Networks
title_fullStr Detecting Total Electron Content Precursors Before Earthquakes by Examining Total Electron Content Images Based on Butterworth Filter in Convolutional Neural Networks
title_full_unstemmed Detecting Total Electron Content Precursors Before Earthquakes by Examining Total Electron Content Images Based on Butterworth Filter in Convolutional Neural Networks
title_sort detecting total electron content precursors before earthquakes by examining total electron content images based on butterworth filter in convolutional neural networks
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2020-01-01
description Daily total electron content (TEC) images created by splitting TEC maps for three time periods from September 1 to 24, 1999; from February 1 to 24, 2003; and from May 1 to 24, 2003 (Taiwan Standard Time [TST]) as training images (inputs) were used to create two convolutional neural network (CNN) models. However, splitting the TEC maps of the three time periods into daily TEC images caused wedge effects. The wedge effects were reduced using a low-pass filter called the Butterworth filter. This resulted in clearer TEC precursors for earthquakes, facilitating the identification of earthquakes of magnitude M<sub>w</sub> &#x2265; 5.0 that exhibited associated TEC precursors during three periods, particularly for the Chi-Chi earthquake of September21, 1999. The results of this study were compared with those of Lin et al. and Lin associated with the Chi-Chi earthquake. Simultaneously, two CNN models that were developed were verified to be rational due to the high accuracy of their predictions. These two models were used to verify each other's accuracies and to demonstrate the reliability of the method in this study. Therefore, statistical analysis was not the aim. The final outputs of the two CNN model were defined as similarities. Similarities, which are larger than 0.5, were defined as TEC precursors of earthquakes. TEC precursors described as temporal TEC multi-precursors (TTMPs) by Zoran et al. were detectable on the 1st, 3rd, and 4th days (that is, on September 17, 18, and 20, 1999, respectively) prior to the Chi-Chi earthquake of September 21, 1999. These results are consistent with those of Liu et al. and Lin. A TEC precursor on May 13, 2003, (TST) was detectable 2 days prior to the earthquake on May 15, 2003, (TST) with the magnitude (M<sub>w</sub>) of 5.52. The low standard deviation (STD) and mean square error (MSE) confirm the reliability of both CNN models. Regarding mechanical principles, the TTMPs related to the Chi-Chi earthquake were caused by an electric field. The cause of the TEC precursor on May 13, 2003, prior to the earthquake on May 15, 2003, was an argument without any corresponding study for comparison.
topic Daily total electron content (TEC) images
convolutional neural network (CNN)
wedge effects
Butterworth filter
temporal TEC multi-precursors (TTMPs)
Chi-Chi earthquake
url https://ieeexplore.ieee.org/document/9113262/
work_keys_str_mv AT jyhwoeilin detectingtotalelectroncontentprecursorsbeforeearthquakesbyexaminingtotalelectroncontentimagesbasedonbutterworthfilterinconvolutionalneuralnetworks
AT juingshianchiou detectingtotalelectroncontentprecursorsbeforeearthquakesbyexaminingtotalelectroncontentimagesbasedonbutterworthfilterinconvolutionalneuralnetworks
_version_ 1724186290344165376