文献类型：期刊文献

英文题名：A nonadditive multiattribute evaluation model using Kansei data

作者：Yan, Hong-Bin[1]; Huynh, Van-Nam[2]; Nakamori, Yoshiteru[2]

机构：[1] School of Business, East China University of Science and Technology, Meilong Road 130, Shanghai, 200237, China; [2] School of Knowledge Science, Japan Advanced Institute of Science and Technology, Asahidai 1-1, Nomi City, Ishikawa, 923-1292, Japan

年份：2011

外文期刊名：Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS

收录：EI(收录号：20112013985007)

语种：英文

外文关键词：Function evaluation - Integral equations

摘要：This study deals with evaluation of products according to the Kansei, which is an individual subjective impression reflecting the aesthetic appeal of products. To do so, after introducing a probabilistic approach to generating Kansei profiles involving fuzzy uncertainty and underlying semantic overlapping, we have proposed a two-phase nonadditive multiattribute Kansei evaluation model based on probabilistic Kansei profiles. First, a target-oriented Kansei evaluation function is proposed to induce nonlinear Kansei satisfaction utility according to a consumer's personal Kansei preference, which provides a good description of the consumer's preference. Second, after formulating a general multiattribute target-oriented (MATO) Kansei evaluation function, a nonadditive MATO Kansei evaluation function is proposed based on an analogy between the general MATO Kansei evaluation function and the Choquet integral. The main advantages of our model are its abilities to deal with good description of personalized Kansei preferences as well as mutual dependence among multiple Kansei preferences. ? 2011 IEEE.