Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (3): 255-262.doi: 10.11896/jsjkx.201200042

• Artificial Intelligence • Previous Articles     Next Articles

Label-based Approach for Dynamic Updating Approximations in Incomplete Fuzzy Probabilistic Rough Sets over Two Universes

XUE Zhan-ao, HOU Hao-dong, SUN Bing-xin, YAO Shou-qian   

  1. College of Computer and Information Engineering,Henan Normal University,Xinxiang,Henan 453007,China
    Key Laboratory of Artificial Intelligence and Personalized Learning in Education of Henan Province,Xinxiang,Henan 453007,China
  • Received:2020-12-03 Revised:2021-05-13 Online:2022-03-15 Published:2022-03-15
  • About author:XUE Zhan-ao,born in 1963,Ph.D,professor,is a senior member of Chinese Artificial Intelligence Association.His main research interests include basic theory of artificial intelligence,rough sets theory,fuzzy sets,and three-way decision theory.
  • Supported by:
    National Natural Science Foundation of China(62076089,61772176) and Scientific and Technological Project of Henan Province of China(182102210078,182102210362).

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Abstract: When the missing values are obtained in incomplete fuzzy probabilistic rough sets over two universes,the time efficiency of the traditional static algorithm for updating approximations in incomplete fuzzy probabilistic rough sets over two universes is too low.To solve this problem,a label-based approach for dynamic updating approximations in incomplete fuzzy probabilistic rough sets over two universes isstudied.Firstly,some definitions of incomplete fuzzy probabilistic rough over two universes are given,then based on the matrix method,a label-based model of incomplete fuzzy probabilistic rough sets over two universes is proposed,and the related theorems are proved.After that,a label-based method for calculating approximations in incomplete fuzzy probabilistic rough sets over two universes is proposed and analyzed.Then,when the missing values are obtained in incomplete fuzzy probabilistic rough sets over two universes,the theorem for dynamic updating its approximations is proved,and a label-based algorithm for dynamic updating approximations in incomplete fuzzy probabilistic rough sets over two universes is designed and analyzed.Finally,the simulation experiments are conducted on six datasets from UCI and three man-made datasets.The experimental results show that the proposed dynamic updating algorithm can improve the time efficiency of updating approximations.Then an example shows that the dynamic algorithm does not affect the correctness of the results when updating approximations,which proves the validity of the proposed dynamic updating algorithm.

Key words: Approximations, Dynamic updating, Incomplete information system over two universes, Label, Rough sets

CLC Number: 

  • TP181
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