期刊文献+

基于感性工学的人机界面多意象评价 被引量:25

Multi-image evaluation for human-machine interface based on Kansei engineering
下载PDF
导出
摘要 为了给人机界面设计提供有效的评价手段,围绕用户对人机界面的感性需求,提出了基于感性工学的人机界面多意象评价方法。首先运用感性工学方法建立感性指标评价体系,在指标权重分配上,通过将灰色关联分析法引入群层次分析(analytic hierarchy process,AHP)法中,利用改进的群AHP法求取综合权重,解决了传统AHP法主观性过强的缺点;同时根据感性工学评价的模糊性,建立了一种直觉模糊集理论和TOPSIS(technique for order preference by similarity to an ideal solution)法相结合的综合评价模型。结合数控机床人机界面设计方案验证了该评价方法的有效性和可行性。该方法对人机界面感性设计与设计评价具有一定的参考意义。 In order to provide an effective evaluation method for human-machine interface design,a multi-image evaluation method for human-machine interface based on Kansei engineering was proposed around the users'perceptual demand for human-machine interface.Firstly,the perceptual evaluation index system based on Kansei engineering was built.In the weight assignment of indexes,the grey correlation analysis was introduced into group analytic hierarchy process(AHP).The comprehensive weight was obtained through the improved group AHP.And thus,the disadvantage of excessive subjectivity of traditional AHP was resolved.Based on vagueness of perceptual evaluation,a comprehensive evaluation model based on intuitionistic fuzzy set and TOPSIS was given.The effectiveness and feasibility of the evaluation method were proved with the design schemes of human-machine interface for CNC machine tools.This method has certain reference significance for Kansei design and design evaluation of human-computer interface.
出处 《工程设计学报》 CSCD 北大核心 2017年第5期523-529,共7页 Chinese Journal of Engineering Design
基金 国家自然科学基金资助项目(51675530 51405505) 航空科学基金资助项目(20145596026)
关键词 人机界面 感性工学 群层次分析 灰色关联分析 直觉模糊集 TOPSIS(technique for order preferenceby SIMILARITY to an IDEAL solution) human-machine interface Kansei engineering group analytic hierarchy process grey correlation analysis intuitionistic fuzzy s e t TOPSIS (technique for order preference by similarity to an ideal solution)
  • 相关文献

参考文献11

二级参考文献122

共引文献269

同被引文献274

引证文献25

二级引证文献114

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部