Article
Computer Science, Information Systems
Zhouming Ma, Jusheng Mi, Yiting Lin, Jinjin Li
Summary: Variable precision rough set (VPRS) has been widely studied as an essential way of knowledge representation and acquisition in uncertainty theory. This paper investigates the corresponding CVPRS model based on a covering-based rough set model, and systematically studies its algebraic structures and properties. An attribute reduction approach is proposed for a covering-based decision information system using the CVPRS model, and the performances of different boundary operators and related indices in these reduction methods are compared. Necessity rules and possibility rules extraction methods corresponding to decision classes are established, and their validity and security are theoretically verified.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Wei Liu, Qihan Liu, Guoju Ye, Dafang Zhao, Yating Guo, Fangfang Shi
Summary: This paper proposes an interval rough number variable precision rough sets model, which combines interval rough number similarity and the concept of variable precision rough sets. The model introduces an error parameter to improve the tolerance of noise data. A maximal positive domain attribute reduction method based on the proposed model is also constructed, which can process the data type of interval rough number without discretization.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Computer Science, Information Systems
Yueli Zhou, Guoping Lin
Summary: This paper introduces the local generalized multigranulation variable precision tolerance rough sets model based on the concept of local multigranulation tolerance rough sets in set-valued decision information systems, and defines the concepts of lower approximate quality, inner and outer importance of attributes.
Article
Mathematics, Applied
Imran Javaid, Shahroz Ali, Shahid Ur Rehman, Aqsa Shah
Summary: This paper investigates the theory of rough set in the context of graphs, using the concept of orbits. The authors introduce the indiscernibility relation based on orbits and prove conditions under which the partitions remain the same. They also study the rough membership functions for various types of graphs and introduce essential sets and discernibility matrices induced by orbits.
Article
Computer Science, Artificial Intelligence
Qiu Jin, Ling-Qiang Li
Summary: This paper introduces 14 types of L-fuzzy variable precision rough sets and provides their axiomatic characterizations, which have not been explored before even in the context of classical rough sets and fuzzy rough sets.
Article
Computer Science, Artificial Intelligence
Jiayue Chen, Ping Zhu
Summary: This paper proposes an extended model called variable precision multigranulation rough sets (VPMGRSs), which introduces rough membership function and approximation parameters from variable precision rough sets (VPRSs) into the multigranulation environment. The relationships between VPMGRSs and other rough sets methods are investigated, along with several VPMGRSs-based attribute reductions. A heuristic algorithm for alpha-lower distribution reduct is also proposed, and its effectiveness and efficiency are demonstrated through a comparative experiment on real datasets.
Article
Computer Science, Artificial Intelligence
Juan Li, Yabin Shao, Xiaoding Qi
Summary: This paper introduces the concept of variable precision into incomplete interval-valued fuzzy information systems and proposes the theory of variable precision rough sets. It explores multiple attribute group decision making problems where attribute weights and expert weights are real numbers and attribute values are interval-valued uncertain linguistic variables, studying knowledge discovery and attribute reduction under a certain degree of misclassification rate. An illustrative example is provided to demonstrate the practicality and effectiveness of the proposed method in comparison to existing methods.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Mathematics, Applied
R. Mareay, Radwan Abu-Gdairi, M. Badr
Summary: This research paper introduces a new approximation structure based on topological near open sets in the approximation space of a rough set. It also presents concepts of topological near open sets and rough concepts, and discusses the properties of the new approximation structure. The paper includes an algorithm for COVID-19 detection based on its side effects, which is believed to be helpful for future detection.
Article
Computer Science, Information Systems
Bin Yu, Yan Hu, Jianhua Dai
Summary: This study introduces a new model based on variable precision rough sets to enhance the fault tolerance of attribute reduction algorithms, and designs a novel algorithm to delete redundant and noise attributes to improve classification accuracy.
INFORMATION SCIENCES
(2023)
Article
Computer Science, Information Systems
Dandan Zou, Yaoliang Xu, Lingqiang Li, Zhenming Ma
Summary: Variable precision (fuzzy) rough sets are generalizations of Pawlak rough sets that handle uncertain and imprecise information well. However, many existing variable precision (fuzzy) rough sets lack the comparable property (CP), which is fundamental in Pawlak rough sets. To address this issue, a novel variable precision fuzzy rough set model with CP is proposed, along with an associated three-way decision model.
INFORMATION SCIENCES
(2023)
Article
Chemistry, Multidisciplinary
Xiaohong Xiang, Zhiqiang Feng, Hao Yuan, Xianping Zeng, Zufu Pan, Xin Li, Quan Li, Xiaohu Huang
Summary: Considering the complexities of the welding process and the variation between individuals in welding experience, this research introduces rough set theory for modeling and quality control of arc welding. A variable precision neighborhood rough-fuzzy method is proposed to enhance the efficiency and adaptability of rough set theory in welding process control. By designing different welding experiments, descriptors such as the tail area coefficient and the length-width ratio of the melt pool are used to characterize the welding process. The results show that the proposed model has excellent stability and effectiveness.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Artificial Intelligence
Ye Du, Bingxue Yao
Summary: This article introduces the covering-based compact and loose variable precision fuzzy rough set models proposed by Zhan and Jiang, as well as their important properties and relationship with the original models. The models are also applied to decision-making problems and validated using a simple example.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2022)
Article
Mathematics, Interdisciplinary Applications
Junliang Du, Sifeng Liu, Yong Liu
Summary: This paper introduces a novel grey variable dual precision rough set model for approximating grey concepts, which can improve the rationality and scientificity of approximation, reduce decision-making risks, and achieve the whitenization of grey objects. The model can be degenerated to traditional models under specific conditions, and it provides a low-risk decision rule for grey decision objects.
GREY SYSTEMS-THEORY AND APPLICATION
(2022)
Article
Computer Science, Theory & Methods
Chun Yong Wang, Lijuan Wan
Summary: The study focuses on granular variable precision fuzzy rough sets based on fuzzy (co)implications to rectify defects, discussing equivalent expressions and composition. Further research looks into rectifying faults using appropriate semicontinuity.
FUZZY SETS AND SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Caihui Liu, Jianying Lai, Bowen Lin, Duoqian Miao
Summary: The classical ID3 decision tree algorithm is not suitable for continuous data and has poor classification effect. In order to address these issues, we propose an improved ID3 algorithm called DIGGI based on variable precision neighborhood rough sets. Experimental results demonstrate that DIGGI outperforms three traditional decision tree algorithms, as well as the recently proposed neighborhood decision tree and variable precision neighborhood decision tree.
APPLIED INTELLIGENCE
(2023)
