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山东大学学报（理学版） ›› 2018, Vol. 53 ›› Issue (8): 1-8.doi: 10.6040/j.issn.1671-9352.4.2018.184

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广义多尺度决策系统的局部最优粒度选择

顾沈明1,2,陆瑾璐2,吴伟志1,2,庄宇斌2   

  1. 1.浙江海洋大学浙江省海洋大数据挖掘与应用重点实验室, 浙江 舟山 316022;2.浙江海洋大学数理与信息学院, 浙江 舟山 316022
  • 收稿日期:2018-04-15 出版日期:2018-08-20 发布日期:2018-07-11
  • 作者简介:顾沈明(1970— ),男,教授,研究方向为粗糙集、粒计算与机器学习. E-mail:gsm@zjou.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(61573321,61773349,41631179,61602415);浙江省自然科学基金资助项目(LY18F030017)

Local optimal granularity selections in generalized multi-scale decision systems

GU Shen-ming1,2, LU Jin-lu2, WU Wei-zhi1,2, ZHUANG Yu-bin2   

  1. 1. Key Laboratory of Oceanographic Big Data Mining &
    Application of Zhejiang Province, Zhejiang Ocean University, Zhoushan 316022, Zhejiang, China;
    2. School of Mathematics, Physics and Information Science, Zhejiang Ocean University, Zhoushan 316022, Zhejiang, China
  • Received:2018-04-15 Online:2018-08-20 Published:2018-07-11

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摘要： 在实际应用中,人们常常选择比较合适的粒度层次来解决相应的问题。在经典的多尺度决策系统和粒度层次构造过程中,属性取值常由人工选择某些固定粒度层次。本文针对广义多尺度决策系统,由属性取值的尺度组合来构造粒度层次,进而研究局部最优粒度的选择问题。首先,介绍了广义多尺度决策系统的概念。然后,在协调的广义多尺度决策系统中定义了最优粒度和局部最优粒度,并给出了基于属性组合的最优粒度与局部最优粒度的选择算法。最后,在不协调的广义多尺度决策系统中引入了广义决策,定义了广义决策最优粒度和广义决策局部最优粒度,并给出了基于广义决策最优粒度与广义决策局部最优粒度选择算法。

关键词: 广义多尺度, 决策系统, 多尺度, 局部最优粒度

Abstract: People tend to choose the appropriate level of granularity to solve problems in application. In the classical multi-scale decision systems, during the process of constructing the levels of granularity, some fixed levels of granularity are selected manually for attribute values. Aiming at generalized multi-scale decision systems in this paper, the levels of granularity are constructed by using the scale combination of attribute values. Furthermore, the selection problems of local optimal granularity are studied. The concept of generalized multi-scale decision systems is introduced firstly. Then, notions of the optimal granularity and the local optimal granularity in consistent generalized multi-scale decision system are defined, and the algorithms for finding optimal granularities and the local optimal granularities are described. Finally, the generalized decisions are introduced to inconsistent generalized multi-granular decision systems, the generalized optimal granularity and the generalized local optimal granularity are defined, and the algorithms for finding the generalized optimal granularity and the generalized local optimal granularity are also investigated.

Key words: decision system, local optimal granularity, multi-scale, generalized multi-scale

中图分类号: 

  • TP18
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