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产品质量屋中用户需求排序的耦合方法
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  • 英文篇名:Coupling Method for User Demand Sequence in Product Quality House
  • 作者:秦建军 ; 路可欣
  • 英文作者:QIN Jianjun;LU Kexin;School of Mechanical-Electronic and Vehicle Engineering,Beijing Key Laboratory of Performance Guarantee on Urban Rail Transit Vehicles, Beijing University of Civil Engineering Architecture;
  • 关键词:模糊需求软集合 ; 隶属度云模型 ; 逆向隶属度云发生器 ; 需求排序 ; 液压四足机器人
  • 英文关键词:fuzzy demand soft set;;membership degree cloud model;;reverse membership cloud generator;;demand sequence;;hydraulic four-legged robot
  • 中文刊名:BJJZ
  • 英文刊名:Journal of Beijing University of Civil Engineering and Architecture
  • 机构:北京建筑大学机电与车辆工程学院城市轨道交通车辆服役性能保障北京市重点实验室;
  • 出版日期:2019-06-30
  • 出版单位:北京建筑大学学报
  • 年:2019
  • 期:v.35;No.117
  • 基金:国家自然科学基金项目(91748211);; 北京市教委科研计划项目(KM201610016003)
  • 语种:中文;
  • 页:BJJZ201902006
  • 页数:7
  • CN:02
  • ISSN:10-1250/TU
  • 分类号:42-48
摘要
针对产品质量屋中用户需求排序的问题,提出模糊需求软集合与隶属度云模型的耦合方法,从模糊性与随机性综合考虑用户需求排序的问题,利用需求模糊隶属度构建模糊需求软集合,消除质量屋在信息传递中的模糊性与不确定性问题,通过逆向隶属度云发生器将定量信息转化为定性概念,基于超熵算子评价法,确定需求重要度最终排序,以液压四足机器人为例,验证了方法的实用性与可行性.
        Aiming at the problem of user demand sequence in product quality house, a coupling method between fuzzy demand soft set and membership degree cloud model is proposed in the paper. The problem of user demand sequence is considered from the perspective of ambiguity and randomness.The fuzzy set of fuzzy requirements is constructed by using the fuzzy membership degree of demand, which eliminates the ambiguity and uncertainty of the quality house in information transmission.The quantitative information is transformed into a qualitative concept by the inverse membership cloud generator, and the final order of the importance of the demand is determined based on the super-entropy operator evaluation method.Taking the hydraulic four-legged robot as an example, the practicability and feasibility of the method are verified.
引文
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