Abstract Multi-Source Information Fusion (MSIF) is a comprehensive and interdisciplinary
subject, and is referred to as, multi-sensor information fusion which was originated in the …

Rough set theory is an efficient tool for dealing with inexact and uncertain information.
Numerous studies have focused on rough set theory and associated methodologies, and in …

The approximation space in rough set theory is important for dealing with uncertainties. As
the information contained in various information systems is constantly updated and changed …

The Bayesian decision-theoretic rough sets propose a framework for studying rough set
approximations using probabilistic theory, which can interprete the parameters from existing …

The main task of local rough set model is to avoid the interference of complicated calculation
and invalid information in the formation of approximation space. In this paper, we first …

Tumor classification based on gene expression levels is important for tumor diagnosis.
Since tumor data in gene expression contain thousands of attributes, attribute selection for …

Abstract The advent of Big Data has seen both the sources and volumes of data increase
rapidly. A multi-source information system can be used to represent information drawn from …

Decision-theoretic rough set provides a new perspective to handle decision-making
problems under uncertainty and risk. The three-way decision theory proposed by Yao is …

The original Pawlak's rough set approach based on indiscernibility relation (single
granularity) has been extended to multigranulation rough set structure in the recent years …

There exist several approaches to rough set approximations in a multigranulation space,
namely, a family of equivalence relations. In this paper, we propose a unified framework to …