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https://doi.org/10.5194/gi-2018-13
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
09 May 2018
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Instrumentation, Methods and Data Systems (GI).
Backpropagation Neural Network as Earthquake Early Warning Tool using a new Elementary Modified Levenberg–Marquardt Algorithm to minimise Backpropagation Errors
Jyh-Woei Lin, Chun-Tang Chao, and Juing-Shian Chiou Department of Electrical Engineering, Southern Taiwan University of Science and Technology, No. 1, Nan-Tai Street, Yungkang Dist., Tainan City, Taiwan
Abstract. A new Elementary Modified Levenberg–Marquardt Algorithm (M-LMA) was used to minimise backpropagation errors in training a backpropagation neural network (BPNN) to predict the records related to the Chi-Chi earthquake from four seismic stations, Station-TAP003, Station-TAP005, Station-TCU084 and Station-TCU078, with the learning rates of 0.3, 0.05, 0.2 and 0.28, respectively. For these four recording stations, the M-LMA has been shown to produce smaller predicted errors compared to LMA. A sudden predicted error could be an indicator for Early Earthquake Warning (EEW), which indicated the initiation of strong motion due to large earthquakes. a trade-off decision-making process with BPNN (TDPB), using two alarms, adjusted the threshold of the magnitude of predicted error without a mistaken alarm. This approach was not necessary to consider the problems of characterising the wave phases and pre-processing, but did not require complex hardware; an existing seismic monitoring network-covered researched area was already sufficient for these purposes.
Citation: Lin, J.-W., Chao, C.-T., and Chiou, J.-S.: Backpropagation Neural Network as Earthquake Early Warning Tool using a new Elementary Modified Levenberg–Marquardt Algorithm to minimise Backpropagation Errors, Geosci. Instrum. Method. Data Syst. Discuss., https://doi.org/10.5194/gi-2018-13, in review, 2018.
Jyh-Woei Lin et al.
Jyh-Woei Lin et al.
Jyh-Woei Lin et al.

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Short summary
This BPNN approach with two alarms was well-suited, and it was not necessary to consider the problems of characterising the wave phases and pre-processing, as stated previously. Furthermore, BPNN was a mature technology, which was expected to develop rapidly in the future, and did not require complex hardware. Determining an initial location and magnitude of the event was not necessary for this technique. An existing seismic monitoring network can be used.
This BPNN approach with two alarms was well-suited, and it was not necessary to consider the...
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