Predicting the friction angle of clays using a multi-layer perceptron neural network enhanced by yeo-johnson transformation and coral reefs optimization

The accurate prediction of the friction angle of clays is crucial for assessing slope stability in engineering applications. This study addresses the importance of estimating the friction angle and presents the development of four soft computing models: YJ-FPA-MLPnet, YJ-CRO-MLPnet, YJ-ACOC-MLPnet,...

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Autori principali:	Libing Yang, Trung Nguyen-Thoi, Trung-Tin Tran
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Elsevier 2024-10-01
Serie:	Journal of Rock Mechanics and Geotechnical Engineering
Soggetti:	Natural hazards Slope stability Friction angle Clay Soft computing models Geotechnical engineering
Accesso online:	http://www.sciencedirect.com/science/article/pii/S1674775524001975
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