View in EDS HTML Full Text PDF Full Text

Identification technique for impulsive seismic motions based on the combination of EAMRCM and SVM.

Saved in:
Bibliographic Details
Title: Identification technique for impulsive seismic motions based on the combination of EAMRCM and SVM.
Authors: Liang, Mingshi1 (AUTHOR), Jiang, Liqiang1 (AUTHOR) jianglq2019@csu.edu.cn, Zhang, Jin2 (AUTHOR), Liu, Xiang2 (AUTHOR)
Source: Advances in Structural Engineering. Oct2026, Vol. 29 Issue 14, p2860-2874. 15p.
Subjects: Support vector machines, Time-frequency analysis, Signal processing, Principal components analysis
Abstract: This study proposes a novel method for identifying impulsive seismic motions by integrating the Enhanced Adaptive Multi-Resolution Chirplet Method (EAMRCM) with a Support Vector Machine (SVM) classifier. EAMRCM provides refined time-frequency representations that effectively extract intricate pulse characteristics from near-fault seismic motion records, thereby enhancing both the accuracy and robustness of the extraction process. Principal Component Analysis (PCA) is employed to distill key features from the seismic data, which is subsequently coupled with an SVM classifier to automatically distinguish between impulsive and non-impulsive events. Compared to existing approaches, the proposed method effectively adapts to complex seismic motion patterns, significantly reduces manual intervention, and enhances both automation and classification accuracy. Simulation tests performed in MATLAB demonstrate that this approach markedly improves the identification accuracy for impulsive seismic events, offering a novel tool and methodological foundation for seismic analysis and disaster mitigation engineering. [ABSTRACT FROM AUTHOR]
Copyright of Advances in Structural Engineering is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 197368732
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Identification technique for impulsive seismic motions based on the combination of EAMRCM and SVM.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Liang%2C+Mingshi%22">Liang, Mingshi</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jiang%2C+Liqiang%22">Jiang, Liqiang</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jianglq2019@csu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Jin%22">Zhang, Jin</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Xiang%22">Liu, Xiang</searchLink><relatesTo>2</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Advances+in+Structural+Engineering%22">Advances in Structural Engineering</searchLink>. Oct2026, Vol. 29 Issue 14, p2860-2874. 15p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Support+vector+machines%22">Support vector machines</searchLink><br /><searchLink fieldCode="DE" term="%22Time-frequency+analysis%22">Time-frequency analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+processing%22">Signal processing</searchLink><br /><searchLink fieldCode="DE" term="%22Principal+components+analysis%22">Principal components analysis</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This study proposes a novel method for identifying impulsive seismic motions by integrating the Enhanced Adaptive Multi-Resolution Chirplet Method (EAMRCM) with a Support Vector Machine (SVM) classifier. EAMRCM provides refined time-frequency representations that effectively extract intricate pulse characteristics from near-fault seismic motion records, thereby enhancing both the accuracy and robustness of the extraction process. Principal Component Analysis (PCA) is employed to distill key features from the seismic data, which is subsequently coupled with an SVM classifier to automatically distinguish between impulsive and non-impulsive events. Compared to existing approaches, the proposed method effectively adapts to complex seismic motion patterns, significantly reduces manual intervention, and enhances both automation and classification accuracy. Simulation tests performed in MATLAB demonstrate that this approach markedly improves the identification accuracy for impulsive seismic events, offering a novel tool and methodological foundation for seismic analysis and disaster mitigation engineering. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Advances in Structural Engineering is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=197368732
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1177/13694332251399294
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 2860
    Subjects:
      – SubjectFull: Support vector machines
        Type: general
      – SubjectFull: Time-frequency analysis
        Type: general
      – SubjectFull: Signal processing
        Type: general
      – SubjectFull: Principal components analysis
        Type: general
    Titles:
      – TitleFull: Identification technique for impulsive seismic motions based on the combination of EAMRCM and SVM.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Liang, Mingshi
      – PersonEntity:
          Name:
            NameFull: Jiang, Liqiang
      – PersonEntity:
          Name:
            NameFull: Zhang, Jin
      – PersonEntity:
          Name:
            NameFull: Liu, Xiang
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 10
              Text: Oct2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 13694332
          Numbering:
            – Type: volume
              Value: 29
            – Type: issue
              Value: 14
          Titles:
            – TitleFull: Advances in Structural Engineering
              Type: main
ResultId 1