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Green technology automotive shape design based on neural networks and support vector regression

Kuo-Kuang Fan (Graduate School of Design Doctoral Program, National Yunlin University of Science and Technology, Yunlin, Taiwan)
Chun-Hui Chiu (Graduate School of Design Doctoral Program, National Yunlin University of Science and Technology, Yunlin, Taiwan and Department of Information and Communication, Southern Taiwan University of Science and Technology, Yunlin, Taiwan)
Chih-Chieh Yang (Department of Multimedia and Entertainment Science, Southern Taiwan University of Science and Technology, Tainan City, Taiwan)

Engineering Computations

ISSN: 0264-4401

Article publication date: 28 October 2014

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Abstract

Purpose

The green technology cars have received much attention due to the air pollution and energy crisis. The purpose of this paper is to increase automotive designers’ understanding of the affective response of consumers about automotive shape design. Consumers’ preference is mainly based on a vehicle's shape features that are traditionally manipulated by designers’ intuitive experience rather than by an effective and systematic analysis. Therefore, when encountering increasing competition in today's automotive market, enhancing car designers’ understanding of consumers’ preferences on the shape features of green technology vehicles to fulfil customers’ demands, has become a common objective for automotive makers.

Design/methodology/approach

In this paper, questionnaires were first used to gather consumer evaluations of certain adjectives describing automobile shape. Then, automotive styling features were systematically examined by numerical definition-based shape representations. Finally, models were individually constructed using support vector regression (SAR), which predicted consumer's affective responses, based on the adjectives selected, and which also incorporated the relationship between consumer's affective responses and automotive styling features.

Findings

In order to predict and suggest the best automotive shape design, the results of this experiment of SVR can provide a basis for the future development of automobiles, particularly for green vehicle design, and support automotive makers in ensuring that automotive shape design to satisfy consumer needs.

Originality/value

SVR is a valuable choice as an evaluation method to be applied in the design field of green vehicles.

Keywords

Citation

Fan, K.-K., Chiu, C.-H. and Yang, C.-C. (2014), "Green technology automotive shape design based on neural networks and support vector regression", Engineering Computations, Vol. 31 No. 8, pp. 1732-1745. https://doi.org/10.1108/EC-11-2012-0294

Publisher

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Emerald Group Publishing Limited

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