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標題Title: Modeling affective responses for product form design based on consumer segmentation and information fusion
作者Authors: 楊智傑,Fang-Chen Hsu..等
上傳單位Department: 多媒體與電腦娛樂科學系
上傳時間Date: 2009-11-16
上傳者Author: 楊智傑
審核單位Department: 多媒體與電腦娛樂科學系
審核老師Teacher: 楊智傑
檔案類型Categories: 論文Thesis
關鍵詞Keyword: Product form design, Kansei engineering, Fuzzy c-means clustering, Support vector regression, 2-additive Choquet integral
摘要Abstract: In the product design field, modeling consumer’s affective responses (ARs) for product form design is very helpful for developing successful products. However, the heterogeneous nature of consumer preference patterns is often neglected in most researches thus the resulting prediction model is of less value for the real-world applications. In the present paper, a Kansei engineering (KE) method is proposed to construct the consensus prediction model of consumer’s ARs based on the concepts of consumer segmentation (CS) and information fusion (IF). First, a fuzzy c-means (FCM) clustering is applied to separate the consumers with heterogeneous preference patterns into homogenous groups. In every consumer group, the relative importance of each consumer and the interaction between pairs of consumers can be determined according to the results of the FCM clustering. Secondly, a state-of-the-art machine learning approach known as “support vector regression (SVR)” is used to construct the individual AR prediction model for each consumer. These individual models have out-performing predictive ability of the ARs for each consumer due to the good generalization performance of the SVR algorithm. Finally, a fuzzy integral aggregation operator, namely the 2-additive Choquet integral, is used to combine the SVR models and also taking into account the relative importance and interaction of consumers in the consumer group. A case study of mobile phone design is also given to demonstrate the effectiveness of the proposed method.

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