计算机应用 ›› 2015, Vol. 35 ›› Issue (7): 1955-1958.DOI: 10.11772/j.issn.1001-9081.2015.07.1955

• 人工智能 • 上一篇    下一篇

基于云模型重叠度的相似性度量

孙妮妮, 陈泽华, 牛昱光, 阎高伟   

  1. 太原理工大学 信息工程学院, 太原 030024
  • 收稿日期:2015-01-20 修回日期:2015-03-10 出版日期:2015-07-10 发布日期:2015-07-17
  • 通讯作者: 阎高伟(1970-),男,山西洪洞人,教授,博士,CCF会员,主要研究方向:智能信息处理、多传感器信息融合,yangaowei@tyut.edu.cn
  • 作者简介:孙妮妮(1988-),女,山东淄博人,硕士研究生,主要研究方向:智能信息处理、云模型; 陈泽华(1974-),女,山西神池人,副教授,博士,CCF会员,主要研究方向:智能信息处理、粒计算; 牛昱光(1958-),男,山西忻州人,副教授,主要研究方向:智能仪表、集散控制系统
  • 基金资助:

    国家自然科学基金资助项目(61450011);山西省自然科学基金资助项目(2011011012-2)。

Similarity measurement between cloud models based on overlap degree

SUN Nini, CHEN Zehua, NIU Yuguang, YAN Gaowei   

  1. College of Information Engineering, Taiyuan University of Technology, Taiyuan Shanxi 030024, China
  • Received:2015-01-20 Revised:2015-03-10 Online:2015-07-10 Published:2015-07-17

摘要:

云模型相似性是用来度量同类概念不同语言值的多个云之间关联程度的方法,相似云及其度量分析方法的提出是对云模型理论的扩展。针对目前相似性度量方法中时间复杂度过高和结果不稳定等不足,提出了一种基于云模型重叠度的相似性度量算法。首先,根据云模型期望、熵、超熵三个数字特征,定义两个云模型的位置关系和逻辑关系;其次,利用两个云的位置和形状特性,计算得到它们间的重叠度;最后,结合云模型重叠度与相似度的关系,将云模型的相似性度量转化为相应重叠部分的定量化描述。通过对时间序列分类实例的应用,验证了该算法在保证结果稳定度和正确率的前提下,与目前时间消耗较低的云模型相似度计算方法(LICM)相比,计算复杂度降低了50%,表明该算法具有可行性和有效性。

关键词: 云模型, 相似性, 重叠度, 逻辑关系, 度量算法, 时间序列

Abstract:

Similarity measurement of cloud model is a method that is used to measure the correlation between cloud models, which have same concept but different languages. Both similar cloud and its measurement analysis method are the extension of cloud model theory. To overcome the disadvantages of high consumption and low precision of calculation, a similarity measure algorithm based on overlap degree was proposed. Firstly, the position and logical relationships between these two clouds were defined according to three digital features: expected value, entropy and hyper entropy; secondly, the overlap degree of two clouds was calculated by using their location and shape features; finally, combined with overlap degree and similarity, the similarity measurement was converted to quantitative description of the overlapping part. In the time series classification experiments with compared Likeness comparing method based on Cloud Model (LICM), the computing consumption of the proposed measurement algorithm is reduced by 50% on the premise of ensuring the stability and accuracy. It is proved to be feasible and effective by the application.

Key words: cloud model, similarity, overlap degree, logical relationship, measurement algorithm, time series

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