Parameter Optimization Control of Multiple Response Process Based on Hesitant Fuzzy Sets

摘要：

　　A robust parameter optimization control method for multi-response process based on hesitant fuzzy sets is proposed.According to the multiresponse process control model,the experimental data is denoised and the effective information is extracted.Finally,the hesitant fuzzy decision matrix is constructed.The fuzzy logic inference algorithm is employed to calculate the comprehensive optimization controllable index of multiple responses in the production process.Based on the main effect method analysis,the optimal combine of control process parameters in multi-response process is searched by establishing an artificial neural network model.The proposed method is put into use for the process parameter optimization in polymer thermal polymerization process.The results show that the parameter optimization method based on hesitation fuzzy sets is feasible and effective.

关键词： Hesitant fuzzy sets Fuzzy logic inference Parameter optimization

作者: Jun Wang Jian-li Yu Feng-ying Gu Hong-Gen Chen

作者单位: Science Institution of Big Data,Zhengzhou University of Aeronautics,Zhengzhou 450046,China School of Management Engineering,Zhengzhou University of Aeronautics,Zhengzhou 450046,China

会议类型: 国际会议

会议名称: 2019中国智能自动化大会(CIA,2019)

会议地点: 江苏镇江

会议语种:英文

页码: 287-295

在线出版日期: 2019-09-20（万方平台首次上网日期，不代表论文的发表时间）