Development of Artificial-Neural-Network-Based Permanent Deformation Prediction Model of Unbound Granular Materials Subjected to Moving Wheel Loading.

Hua, Wenjun; Yu, Qunding; Xiao, Yuanjie; Li, Wenqi; Wang, Meng; Chen, Yuliang; Li, Zhiyong

Hua, Wenjun; Yu, Qunding; Xiao, Yuanjie; Li, Wenqi; Wang, Meng; Chen, Yuliang; Li, Zhiyong.

Afiliación

Hua W; School of Civil Engineering, Central South University, Changsha 410075, China.
Yu Q; School of Civil Engineering, Central South University, Changsha 410075, China.
Xiao Y; Urban Rail and Underground Engineering Design and Research Institute, China Railway Siyuan Survey and Design Group Co., Ltd., Wuhan 430063, China.
Li W; School of Civil Engineering, Central South University, Changsha 410075, China.
Wang M; MOE Key Laboratory of Engineering Structures of Heavy Haul Railway, Central South University, Changsha 410075, China.
Chen Y; School of Civil Engineering, Central South University, Changsha 410075, China.
Li Z; School of Civil Engineering, Central South University, Changsha 410075, China.

Materials (Basel) ; 15(20)2022 Oct 19.

Article en En | MEDLINE | ID: mdl-36295369

Palabras clave

artificial neural network (ANN); cyclic triaxial test; permanent deformation; prediction model; unbound granular materials

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Materials (Basel) Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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