Abstract
AbstractA robust parameter optimization control method for multi-response process based on hesitant fuzzy sets is proposed. According to the multi-response 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.KeywordsHesitant fuzzy setsFuzzy logic inferenceParameter optimization
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