A scientometrics review of conventional and soft computing methods in the slope stability analysis
Predicting 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 re...
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Frontiers Media SA
2025
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| author | Ahmad F. Tang X.-W. Ahmad M. Najeh T. Gamil Y. |
| author2 | 57204650618 |
| author_facet | 57204650618 Ahmad F. Tang X.-W. Ahmad M. Najeh T. Gamil Y. |
| author_sort | Ahmad F. |
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| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Predicting 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. |
| format | Review |
| id | my.uniten.dspace-36961 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2025 |
| publisher | Frontiers Media SA |
| record_format | dspace |
| spelling | my.uniten.dspace-369612025-03-03T15:46:08Z A scientometrics review of conventional and soft computing methods in the slope stability analysis Ahmad F. Tang X.-W. Ahmad M. Najeh T. Gamil Y. 57204650618 55725174500 58731610900 57220642186 57191379149 Predicting 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. Final 2025-03-03T07:46:08Z 2025-03-03T07:46:08Z 2024 Review 10.3389/fbuil.2024.1373092 2-s2.0-85205794136 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205794136&doi=10.3389%2ffbuil.2024.1373092&partnerID=40&md5=201989483db088dd1fa3a45f69eb7624 https://irepository.uniten.edu.my/handle/123456789/36961 10 1373092 All Open Access; Gold Open Access Frontiers Media SA Scopus |
| spellingShingle | Ahmad F. Tang X.-W. Ahmad M. Najeh T. Gamil Y. A scientometrics review of conventional and soft computing methods in the slope stability analysis |
| title | A scientometrics review of conventional and soft computing methods in the slope stability analysis |
| title_full | A scientometrics review of conventional and soft computing methods in the slope stability analysis |
| title_fullStr | A scientometrics review of conventional and soft computing methods in the slope stability analysis |
| title_full_unstemmed | A scientometrics review of conventional and soft computing methods in the slope stability analysis |
| title_short | A scientometrics review of conventional and soft computing methods in the slope stability analysis |
| title_sort | scientometrics review of conventional and soft computing methods in the slope stability analysis |
| url_provider | http://dspace.uniten.edu.my/ |