东北大学学报:自然科学版 ›› 2018, Vol. 39 ›› Issue (8): 1169-1174.DOI: 10.12068/j.issn.1005-3026.2018.08.021

• 机械工程 • 上一篇    下一篇

云制造环境下知识资源的评价与选择

陈友玲, 黄典, 张岳园, 赵金鹏   

  1. (重庆大学 机械传动国家重点实验室, 重庆400044)
  • 收稿日期:2017-03-20 修回日期:2017-03-20 出版日期:2018-08-15 发布日期:2018-09-12
  • 通讯作者: 陈友玲
  • 作者简介:陈友玲(1964-),女,重庆人,重庆大学教授,博士生导师.冯明杰(1971-), 男, 河南禹州人, 东北大学副教授; 王恩刚(1962-), 男, 辽宁沈阳人, 东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(71671020),国家自然科学基金资助项目(51171041).

Evaluation and Selection for Knowledge Resources in Cloud Manufacturing Environment

CHEN You-ling, HUANG Dian, ZHANG Yue-yuan, ZHAO Jin-peng   

  1. State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing 400044, China.
  • Received:2017-03-20 Revised:2017-03-20 Online:2018-08-15 Published:2018-09-12
  • Contact: HUANG Dian
  • About author:-
  • Supported by:
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摘要: 为了解决云制造环境下知识资源的选择问题,从知识资源提供方服务能力的角度,提出了一种基于知识服务能力值的选择模型.该模型从知识资源供需双方自身特性出发,从企业维、服务维、交互维三维度建立知识资源提供方服务能力评价体系,利用变精度粗糙集算法计算各评价指标的权重,利用敏感系数修正用户在实际情况下的偏好,最终求得所有候选资源的知识服务能力值;以此为依据指导云平台为用户选择最佳的知识资源供应方.实例表明,该模型能够从大量候选资源中推理出最佳的知识资源推荐给用户.

关键词: 云制造, 知识资源, 知识服务能力值, 偏好修正, 变精度粗糙集

Abstract: In order to solve the problem of selecting knowledge resources in the cloud manufacturing environment, a selection model is presented based on the capacity of knowledge service from the perspective of knowledge resources suppliers’ service capacity. Through establishing the system for evaluating the capacity of knowledge service, the variable precision roughness set algorithm is utilized to calculate the weight of each evaluation index, and the sensitivity coefficient is used to revise users’ preference in actual cases. All the candidates’ capacities of knowledge service are obtained, based on which to guide the cloud platform to select the best supplier for users. Finally, examples are given to prove that the model can select the best supplier for users.

Key words: cloud manufacturing, knowledge resource, capacity of knowledge service, preference revision, variable precision roughness set

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