Incomplete Multigranulation Rough Set

Qian, Yuhua; Liang, Jiye; Dang, Chuangyin

doi:10.1109/tsmca.2009.2035436

Cited by 307 publications

(125 citation statements)

References 49 publications

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“…In the following, we will use a venture investment issue which was showed in Ref. 16 , to illustrate the three global measurements.…”

Section: Theorem 10mentioning

confidence: 99%

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Local and Global Measurements of MGRS Rules

Yang¹,

Zhang²,

Yang³

2012

IJCIS

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Since the multigranulation rough sets (MGRS) can be considered as the compositions of multiindependent Pawlak's rough sets, the multigranulation rough set rules (MGRS rules) are then the compositions of decision rules, which are supported by multi-independent Pawlak's rough sets. To measure MGRS rules, both the local and global views are employed in this paper. In local view, the support, certainty and coverage factors are proposed to measure MGRS rules, which are support by an object; while in global view, these three factors are proposed to measure MGRS rules, which are coexisting in a decision system. The necessary conditions for these factors to achieve maximal and minimal values are also addressed. Some numerical examples are employed to substantiate the conceptual arguments.

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“…In the following, we will use a venture investment issue which was showed in Ref. 16 , to illustrate the three global measurements.…”

Section: Theorem 10mentioning

confidence: 99%

“…Presently, the multigranulation approach progressing rapidly. For example, in Qian et al's M-GRS theory, there are two different models: one is the optimistic MGRS 15,16 and the other is the pessimistic MGRS 17 . Following Qian et al's work, Yang et al generalized the MGRS into fuzzy and incomplete environments in Ref.…”

Section: Introductionmentioning

confidence: 99%

Local and Global Measurements of MGRS Rules

Yang¹,

Zhang²,

Yang³

2012

IJCIS

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“…From the viewpoint of the granular computing, an equivalence relation on the universe can be regarded as a granulation, and a partition (induced by the equivalence relation) on the universe can be regarded as a granulation space, a equivalence class can be regarded as a knowledge granule [24,25,26]. So, the above expanded rough set models are based on single granulation, they also called the single granulation rough sets.…”

Section: Introductionmentioning

confidence: 99%

“…So, the above expanded rough set models are based on single granulation, they also called the single granulation rough sets. However, it should be noticed that in [25,27,28], Qian et al argued that we often need to describe concurrently a target concept through multiple granulations on the universe according to a user's requirements or targets of problem solving. Therefore, they proposed the concept of Multigranulation Rough Set (MGRS) model.…”

Section: Introductionmentioning

confidence: 99%

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Incomplete Variable Multigranulation Rough Sets Decision

Zhang¹,

Wang²,

Yang³

et al. 2014

Appl. Math. Inf. Sci.

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Abstract:Recently, a multigranulation rough set (MGRS) has become a new direction in rough set theory, which is different from the Pawlake's rough set since the former takes multiple granulations on the universe into account. In this paper, by analyzing the limitations of optimistic multigranulation rough set (OMGRS) and pessimistic multigranulation rough set (PMGRS) in incomplete information system, the incomplete variable multigranulation rough set (VMGRS) is proposed, and the relationships among VMGRS, OMGRS and PMGRS are deeply explored, From the properties, it can be found that OMGRS and PMGRS are the special cases compared to our VMGRS. Furthermore, several important measurements are introduced into the VMGRS; it is shown that the measurements of the VMGRS are between the measurements of OMGRS and PMGRS. Finally, some numerical examples are employed to substantiate the conceptual arguments.

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Rough‐Fuzzy Hybridization and Granular Computing

Maji

Pal

2012

Rough‐Fuzzy Pattern Recognition

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Incomplete Multigranulation Rough Set

Cited by 307 publications

References 49 publications

Local and Global Measurements of MGRS Rules

Local and Global Measurements of MGRS Rules

Incomplete Variable Multigranulation Rough Sets Decision

Rough‐Fuzzy Hybridization and Granular Computing

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