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机译:基于决策树的机器学习可优化复合材料圆柱体的叠层堆叠,以实现最大屈曲载荷和最小瑕疵敏感性
Tech Univ Carolo Wilhelmina Braunschweig, Inst Adaptron & Funct Integrat, Langer Kamp 6, D-38106 Braunschweig, Germany;
German Aerosp Ctr DLR, Inst Composite Struct & Adapt Syst, Lilienthalpl 7, D-38108 Braunschweig, Germany;
German Aerosp Ctr DLR, Inst Composite Struct & Adapt Syst, Lilienthalpl 7, D-38108 Braunschweig, Germany;
German Aerosp Ctr DLR, Inst Composite Struct & Adapt Syst, Lilienthalpl 7, D-38108 Braunschweig, Germany;
Tech Univ Carolo Wilhelmina Braunschweig, Inst Adaptron & Funct Integrat, Langer Kamp 6, D-38106 Braunschweig, Germany|German Aerosp Ctr DLR, Inst Composite Struct & Adapt Syst, Lilienthalpl 7, D-38108 Braunschweig, Germany;
Open Hybrid LabFactory eV, Fraunhofer Inst, Hermann Munch Str 2, D-38440 Wolfsburg, Germany;
Buckling; Robust design; Knockdown factor; Imperfection sensitivity; Composite shell; Postbuckling; Optimization; Machine learning; Decision tree;
机译:使用无参数优化算法的最大屈曲载荷能力的复合层压板最佳堆叠顺序设计
机译:使用参数优化算法的最大屈曲负载能力的复合层压板的最佳堆叠序列设计
机译:基于遗传算法的最大屈曲载荷优化叠层复合网格板堆垛顺序
机译:层压复合圆柱壳屈曲的缺陷敏感性分析
机译:复合材料板和圆柱壳的屈曲优化:不确定的载荷组合。
机译:基于瞬态热传导配置文件和基于机器学习的数据分析的复合层压化分层检测
机译:基于决策树的机器学习,优化复合缸的层压板堆叠,以实现最大屈曲负荷和最小缺陷敏感性