A Modified Back Propagation Artificial Neural Network Model Based on Genetic Algorithm to Predict the Flow Behavior of 5754 Aluminum Alloy.

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作者： Changqing,Huang ^[1] ; Xiaodong,Jia ^[2] ; Zhiwu,Zhang ^[3]

作者单位： Light Alloy Research Institute, Central South University, Changsha 410083, China. huangcq64@csu.edu.cn. ^[1] State Key Laboratory of High-performance Complicated Manufacturing, Central South University, Changsha 410083, China. huangcq64@csu.edu.cn. ^[2] School of Mechanical and Electrical Engineering, Central South University, Changsha 410083, China. huangcq64@csu.edu.cn. ^[3] Light Alloy Research Institute, Central South University, Changsha 410083, China. 163811003@csu.edu.cn. ^[4] State Key Laboratory of High-performance Complicated Manufacturing, Central South University, Changsha 410083, China. 163811003@csu.edu.cn. ^[5] Light Alloy Research Institute, Central South University, Changsha 410083, China. 163812020@csu.edu.cn. ^[6] State Key Laboratory of High-performance Complicated Manufacturing, Central South University, Changsha 410083, China. 163812020@csu.edu.cn. ^[7]

关键词 5754 aluminum alloy artificial neural network constitutive model dynamic softening mechanism genetic algorithm hot compressive

DOI 10.3390/ma11050855

PMID 29883394

发布时间 2020-09-30

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