,Ensemble RBF modeling technique for quality design

• 作 者: Linhan Ouyang Liangqi Wan Chanseok Park Jianjun Wang Yizhong Ma
• 机 构: College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing, 21
• 出 处: 管理科学学报（英文）
• 发表日期: 2019年2期
• 关键词: RBF model Ensemble model Model selection Pareto chart Process optimization

This paper proposes an ensemble radial basis function neural network that selects important RBF subsets based on Pareto chart using Bootstrap samples. Then, the analysis of variance method is used to determine the choice of the unequal/equal weights. The effectiveness of the proposed technique is illustrated with a micro-drilling process. The comparison results show that the proposed technique can not only improve the model prediction performance, but also generate a reliable scheme for quality design.