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A Systematic Method for Selecting Critical Product Form Features Regarding Consumers' Image Perceptions

机译:选择有关消费者形象感知的关键产品形式特征的系统方法

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This study proposes a product form feature (PFF) selection method based on a numerical definition-based approach (NDA) and the consumers' image perceptions (CIPs). In the proposed approach, NDA is used to generate an explicit numerical definition of the product form design and the corresponding CIPs are determined by means of a semantic differential experiment. A CIP prediction model is constructed using support vector regression (SVR) techniques. Finally, the feature selection method, namely SVR with support vector machine recursive feature elimination (SVM-RFE), is used to identify the critical form features. The validity of the feature selection method is demonstrated using a knife design for illustration purposes. The result shows that the proposed method provides product designers with a powerful tool for systematically selecting the critical form features and evaluating their respective effects on the consumers' image perceptions.
机译:这项研究提出了一种基于基于数字定义的方法(NDA)和消费者的图像感知(CIP)的产品形式特征(PFF)选择方法。在提出的方法中,使用NDA生成产品形式设计的显式数值定义,并通过语义差异实验确定相应的CIP。使用支持向量回归(SVR)技术构建CIP预测模型。最后,使用特征选择方法,即具有支持向量机递归特征消除功能的SVR(SVM-RFE)来识别关键形式特征。为了说明的目的,使用刀设计来证明特征选择方法的有效性。结果表明,所提出的方法为产品设计师提供了一个强大的工具,可以系统地选择关键的形式特征并评估它们各自对消费者形象感知的影响。

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