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Liu Z, Chen C, Ma Q. Category-aware optimal transport for incomplete data classification. Inf Sci (N Y) 2023. [DOI: 10.1016/j.ins.2023.03.107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
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Yang HL, Ren HH. A three-way decision model on incomplete single-valued neutrosophic information tables. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2022. [DOI: 10.3233/jifs-221942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
In this paper, we focus on the three-way decision model on incomplete single-valued neutrosophic information tables. Firstly, we define the minimum and maximum similarity measures between single-valued neutrosophic numbers (SVNNs) which may contain unknown values. On this basis, the notion of θ-weak similarity measure is given. Then, we introduce the conception of an incomplete single-valued neutrosophic information table (ISVNIT). For an incomplete single-valued neutrosophic information table, a new similarity relation is proposed based on the θ-weak similarity measure. Some properties are also studied. By using Bayesian decision theory and this similarity relation, we construct a three-way decision model on an ISVNIT. Finally, an example of choosing product service providers is explored to illustrate the rationality and feasibility of the proposed model. We also discuss the influence of parameters in the model on decision results.
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Affiliation(s)
- Hai-Long Yang
- School of Mathematics and Statistics, Shaanxi Normal University, Xi’an, P.R. China
| | - Huan-Huan Ren
- School of Mathematics and Statistics, Shaanxi Normal University, Xi’an, P.R. China
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Xu J, Xin P, Zhang Y. Three-way neighborhood based stream computing for incomplete hybrid information system. Knowl Based Syst 2022. [DOI: 10.1016/j.knosys.2022.110232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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Accelerating Update of Variable Precision Multigranulation Approximations While Adding Granular Structures. INFORMATION 2022. [DOI: 10.3390/info13110541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
In multigranulation environments, variable precision multigranulation rough set (VPMGRS) is a useful framework that has a tolerance for errors. Approximations are basic concepts for knowledge acquisition and attribute reductions. Accelerating update of approximations can enhance the efficiency of acquiring decision rules by utilizing previously saved information. In this study, we focus on exploiting update mechanisms of approximations in VPMGRS with the addition of granular structures. By analyzing the basic changing trends of approximations in VPMGRS, we develop accelerating update mechanisms for acquiring approximations. In addition, an incremental algorithm to update variable precision multigranulation approximations is proposed when adding multiple granular structures. Finally, extensive comparisons elaborate the efficiency of the incremental algorithm.
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Jiang H, Hu BQ. On two new types of fuzzy rough sets via overlap functions and corresponding applications. Inf Sci (N Y) 2022. [DOI: 10.1016/j.ins.2022.11.058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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