摘要
建立了用户对产品的感性评价与模糊D-S证据理论的关联模型;利用产生式规则来表达用户感性评价知识;以产品的部件外形来构成推理的证据部分;以感性词汇集及相应的语意差分值来定义规则的目标集.通过模糊D-S证据理论的规则合成算法,最终获得了用户对整体产品评价及可靠度.该方法能有效地解决感性认知中的"未知性"及评价目标的单一性问题,并在以汽车为例的概念设计中得到较好应用.
To evaluate products by using Kansei words, an approach was introduced based on fuzzy Dempster-Shafer theory （DST） in product Kansei evaluation system （KES）. Kansei knowledge is represented as ＂if-then＂ rules, and evidences are composed of form features of products. The objective set represented by Fuzzy Set is defined with Kansei vocabulary and its relative semantic difference （SD） scale. The ultimate reliability of Kansei knowledge and Kansei evaluation of the products are acquired through a rule combination algorithm based on fuzzy DST. The proposed method was applied successfully in Autofront-view conceptual design case.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2008年第3期361-365,共5页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60475025)
教育部博士点基金(20050335096)
浙江省教育厅科研项目(20070920).
关键词
感性工学语意差分法模糊D-S证据理论
Kansei engineering
semantic differential method
fuzzy Dempster-Shafer evidence theory
