Multi-source information fusion based on rough set theory: A review

P Zhang, T Li, G Wang, C Luo, H Chen, J Zhang… - Information …, 2021 - Elsevier
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 …

Pythagorean fuzzy set: state of the art and future directions

X Peng, G Selvachandran - Artificial Intelligence Review, 2019 - Springer
Pythagorean fuzzy set, generalized by Yager, is a new tool to deal with vagueness
considering the membership grade μ μ and non-membership ν ν satisfying the condition μ …

Fuzzy intelligence learning based on bounded rationality in IoMT systems: a case study in Parkinson's disease

C Zhang, J Ding, J Zhan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As a cause of interfering with routine activities, freezing of gait (FOG) is a severe syndrome
of Parkinson's disease (PD) and usually performs as an abrupt and momentary inability to …

Three-way cognitive concept learning via multi-granularity

J Li, C Huang, J Qi, Y Qian, W Liu - Information sciences, 2017 - Elsevier
The key strategy of the three-way decisions theory is to consider a decision-making problem
as a ternary classification one (ie acceptance, rejection and non-commitment). Recently, this …

Covering based multigranulation (I, T)-fuzzy rough set models and applications in multi-attribute group decision-making

J Zhan, B Sun, JCR Alcantud - Information Sciences, 2019 - Elsevier
By means of a fuzzy logical implicator and a t-norm (respectively denoted I and T), we
introduce covering based multigranulation (I, T)-fuzzy rough set models from fuzzy β …

[HTML][HTML] A survey on rough set theory and its applications

Q Zhang, Q Xie, G Wang - CAAI Transactions on Intelligence Technology, 2016 - Elsevier
After probability theory, fuzzy set theory and evidence theory, rough set theory is a new
mathematical tool for dealing with vague, imprecise, inconsistent and uncertain knowledge …

Sequential three-way decision and granulation for cost-sensitive face recognition

H Li, L Zhang, B Huang, X Zhou - Knowledge-Based Systems, 2016 - Elsevier
Many previous studies on face recognition attempted to seek a precise classifier to achieve
a low misclassification error, which is based on an assumption that all misclassification costs …

MFGAD: Multi-fuzzy granules anomaly detection

Z Yuan, H Chen, C Luo, D Peng - Information Fusion, 2023 - Elsevier
Unsupervised anomaly detection is an important research direction in the process of
unsupervised knowledge acquisition. It has been successfully applied in many fields, such …

Dynamic updating approximations of local generalized multigranulation neighborhood rough set

W Xu, K Yuan, W Li - Applied Intelligence, 2022 - Springer
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 …

Multigranulation decision-theoretic rough sets

Y Qian, H Zhang, Y Sang, J Liang - International journal of approximate …, 2014 - Elsevier
The Bayesian decision-theoretic rough sets propose a framework for studying rough set
approximations using probabilistic theory, which can interprete the parameters from existing …