A BP Neural Network Product Design Optimization Model Based on Emotional Design and Sustainable Product Design
Source abstract
Abstract
The objective of this study is to investigate the impact of emotional design and sustainable product design on user experience and satisfaction. Additionally, the study aims to optimize the combination efficiency and material selection methods of these two design approaches, extracting optimization parameters based on emotional and sustainable product design principles. By analyzing user satisfaction through questionnaires, various product indicators were examined. The study ultimately establishes a BP neural network optimization model by analyzing the design elements of different products and the satisfaction levels of various indicators. This BP neural network design optimization model, integrating emotional and sustainable design, demonstrates an accuracy rate of over 95% in predicting user satisfaction for different design schemes. Upon examining the emotional design and sustainable design parameter tables following data standardization, and analyzing various product models, it was concluded that the rate of change in each design parameter significantly impacts the satisfaction of each product indicator, highlighting the importance of these parameters in product design optimization.
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Research context
OpenAlex topics: Color perception and design
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Sustainable Design & Material Innovation, Graduate School of Kookmin University, Kookmin University, Seoul 02707, Republic of Korea
Department of Visual Communication and Digital Media, School of Design Technology Graduate School, Guangxi Normal University, Guilin 541001, China
References (39)
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