Towards an Optimized Artificial Neural Network for Predicting Flow Stress of In718 Alloys at High Temperatures.

Zhang, Chunbo; Shi, Qingyu; Wang, Yihe; Qiao, Junnan; Tang, Tianxiang; Zhou, Jun; Liang, Wu; Chen, Gaoqiang

Zhang, Chunbo; Shi, Qingyu; Wang, Yihe; Qiao, Junnan; Tang, Tianxiang; Zhou, Jun; Liang, Wu; Chen, Gaoqiang.

Afiliación

Zhang C; Harbin Welding Institute Limited Company, Harbin 150028, China.
Shi Q; Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.
Wang Y; Smart Manufacturing Thrust, Systems Hub, Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511466, China.
Qiao J; Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.
Tang T; Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.
Zhou J; Harbin Welding Institute Limited Company, Harbin 150028, China.
Liang W; Harbin Welding Institute Limited Company, Harbin 150028, China.
Chen G; Department of Mechanical Engineering, Tsinghua University, Beijing 100084, China.

Materials (Basel) ; 16(7)2023 Mar 27.

Article en En | MEDLINE | ID: mdl-37048956

Palabras clave

accuracy; artificial neural network; flow stress; nickel alloys

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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: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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