Information fusion and attribute reduction for multi-source incomplete mixed data via conditional information entropy and D-S evidence theory-Reference-Cited by-同舟云学术

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Information fusion and attribute reduction for multi-source incomplete mixed data via conditional information entropy and D-S evidence theory

Published:2024-01 Issue: Volume:151 Page:111149
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Li Zhaowen,Zhang Qinli^ORCID,Liu Suping,Peng Yichun,Li Lulu

Publisher

Elsevier BV

Subject

Software

Reference34 articles.

1. Information fusion in rough set theory: An overview;Wei;Inf. Fusion,2019

2. A novel approach to information fusion in multi-source datasets: a granular computing viewpoint;Xu;Inf. Sci.,2017

3. Decision-theoretic rough set model of multi-source decision systems;Sang;Int. J. Mach. Learn. Cybern.,2018

4. A data-level fusion model for unsupervised attribute selection in multi-source homogeneous data;Zhang;Inf. Fusion,2022

5. Evaluate the reliability of information sources using the non-parametric plausibility ReliefF algorithm for multi-source information fusion;Zhang;Appl. Soft Comput.,2023

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