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A scientometrics review of conventional and soft computing methods in the slope stability analysis

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dc.citedby1
dc.contributor.authorAhmad F.en_US
dc.contributor.authorTang X.-W.en_US
dc.contributor.authorAhmad M.en_US
dc.contributor.authorNajeh T.en_US
dc.contributor.authorGamil Y.en_US
dc.contributor.authorid57204650618en_US
dc.contributor.authorid55725174500en_US
dc.contributor.authorid58731610900en_US
dc.contributor.authorid57220642186en_US
dc.contributor.authorid57191379149en_US
dc.date.accessioned2025-03-03T07:46:08Z
dc.date.available2025-03-03T07:46:08Z
dc.date.issued2024
dc.description.abstractPredicting slope stability is important for preventing and mitigating landslide disasters. This paper examines the existing approaches for analyzing slope stability. There are several established conventional approaches for slope stability analysis that can be applied in this context. However, in recent decades, soft computing methods has been extensively developed and employed in stochastic slope stability analysis, notably as surrogate models to improve computing efficiency in contrast to traditional approaches. Soft computing methods can deal with uncertainty and imprecision, which may be quantified using performance indices like coefficient of determination, in regression and accuracy in classification. This review study focuses on conventional methods such as the Bishop?s method and Janbu?s method, as well as soft computing models such as support vector machine, artificial neural network, Gaussian process regression, decision tree, etc. The advantages and limitations of soft computing techniques in relation to conventional methods have also been thoroughly covered in this paper. The achievements of soft computing methods are summarized from two aspects?predicting factor of safety and classification of slope stability. Key potential research challenges and future prospects are also given. Copyright ? 2024 Ahmad, Tang, Ahmad, Najeh and Gamil.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo1373092
dc.identifier.doi10.3389/fbuil.2024.1373092
dc.identifier.scopus2-s2.0-85205794136
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85205794136&doi=10.3389%2ffbuil.2024.1373092&partnerID=40&md5=201989483db088dd1fa3a45f69eb7624
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36961
dc.identifier.volume10
dc.publisherFrontiers Media SAen_US
dc.relation.ispartofAll Open Access; Gold Open Access
dc.sourceScopus
dc.sourcetitleFrontiers in Built Environment
dc.titleA scientometrics review of conventional and soft computing methods in the slope stability analysisen_US
dc.typeReviewen_US
dspace.entity.typePublication
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