A Study on Prediction Model Based on Support Vector Regression for Green Technology Automotive Form Design 2011-01-0467
Due to the air pollution and energy crisis, the added values to environmental protection from the green technology passenger cars have received scrutiny by consumers. In order to enhance the comprehension of consumers' acceptance in green technology passenger cars, the goal of this study is to promote automotive designer's understanding on the affective response of consumers on automotive form design. In general, consumers' preference is mainly based on the vehicles' form features that are traditionally manipulated by designers' intuitive experience rather than an effective and systematic analysis. Therefore, when encountered the increasing competition in automotive market nowadays, enhancing the car designer's understanding of consumers' preference on the form features of green technology passenger cars to fulfill customers' demands has become a common objective among automotive makers.
In this paper, adjective evaluation data of customers were screened first from questionnaire to obtain baseline information. Secondly, automotive style features were systematically examined by numerical definition-based form representation. Finally, a predictive model based on these “adjectives” selected earlier was constructed using support vector regression (SVR) to incorporate the relationship between customers' affective responses and automotive style features. The experimental results can be used for the future development of automotive, especially work as references of green technology passenger cars form design and support automotive makers to bring visual expectation on automotive form design to consumers' experience.