Jisuanji kexue (Mar 2022)

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

DOI
https://doi.org/10.11896/jsjkx.201200042
Journal volume & issue
Vol. 49, no. 3
pp. 255 – 262

Abstract

Read online

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.

Keywords