Rough set and PSO-based ANFIS approaches to modeling customer satisfaction for affective product design. Issue 3 (August 2015) - Jiang, Huimin; Kwong, C.K.; Siu, K.W.M.; Liu, Y.
Highlights Rough set and PSO-based ANFIS approaches are proposed to model customer satisfaction in affective product design. Rough set is used to simplify ANFIS structure and PSO is introduced to enhance the accuracy of modeling. Generated fuzzy rules address fuzziness exists in customer survey data. Generated models show the nonlinear relationships between affective responses and design attributes. The proposed approaches outperform the FLSR, FR, and GP-FR in terms of training errors and validation errors.