On an optimization representation of decision-theoretic rough set model

Jia, Xiuyi; Tang, Zhenmin; Liao, Wenhe; Shang, Lin

doi:10.1016/j.ijar.2013.02.010

Cited by 123 publications

(37 citation statements)

References 46 publications

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“…Rough sets, a new-style mathematical tools, are widely applied to handle incertitude and incomplete data in many fields, such as cognitive science, patter recognition, machine learning, and so on; for example in [2][3][4] the applications of rough sets were given. In addition, an equivalence relation (briefly, ER), as an indispensable part in Pawlak rough sets, is also investigated highly by many researchers.…”

Section: Introductionmentioning

confidence: 99%

A study on soft rough semigroups and corresponding decision making applications

2017

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Abstract:In this paper, we study a kind of soft rough semigroups according to Shabir's idea. We define the upper and lower approximations of a subset of a semigroup. According to Zhan's idea over hemirings, we also define a kind of new C -soft sets and C C -soft sets over semigroups. In view of this theory, we investigate the soft rough ideals (prime ideals, bi-ideals, interior ideals, quasi-ideals, regular semigroups). Finally, we give two decision making methods: one is for looking a best a parameter which is to the nearest semigroup, the other is to choose a parameter which keeps the maximum regularity of regular semigroups.

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Section: Introductionmentioning

confidence: 99%

A study on soft rough semigroups and corresponding decision making applications

2017

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“…Greco et al (2007) combine the decision-theoretic rough set with the dominance-based rough set and then give a new generalized rough set model. Ma and Sun (2012a, b) study the decision-theoretic rough set theory over two universes based on the idea of the classical decision-theoretic rough set (Sun et al 2012;Jia et al 2014). At the same time, there are other studies on both rough set models over two universes and decision-theoretic rough set and also presented many applications in the existing literatures.…”

Section: Introductionmentioning

confidence: 99%

An approach to emergency decision making based on decision-theoretic rough set over two universes

Sun

Zhao

2015

Soft Comput

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Emergency decision making is still an important issue in unconventional emergency management research. Although many studies have been written on this topic, they remain political and qualitative, and it is difficult to make them operational in practice. Therefore, this article proposes a decision-theoretic rough set over two universes as an approach for solving this difficulty. The proposed approach integrates rough set theory over two universes using a Bayesian decision-making technique. In this study, emergency decision making is considered as a multiple-criteria ranking or multiple-criteria selection problem with multigranularity linguistic assessment information. A Bayesian decision process based on linguistic description with qualitative data over two universes is first presented to construct the decision model and approach, and then the decision-theoretic rough set theory over two universes is taken to induce a set of decision rules that satisfy minimum risk of loss conditions. These rules can easily give the optimal decision results with minimum risk of loss by considering online information, realistic scenarios, and the dynamic characteristic of unconventional emergency events as they develop. Finally, the steps and the basic principle of the proposed method are illustrated by a numerical example with the background of emergency decision making.

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“…Liang et al [10] proposed triangular fuzzy DTRS by generalizing the precise value of loss function to triangular fuzzy number. Jia et al [5] proposed an optimization representation of DTRS model. Zhou [41] constructed a new formulation of multi-class DTRS.…”

Section: Introductionmentioning

confidence: 99%

Multigranulation decision-theoretic rough sets in incomplete information systems

Yang

Guo

2015

Int. J. Mach. Learn. & Cyber.

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We study multigranulation decision-theoretic rough sets in incomplete information systems. Based on Bayesian decision procedure, we propose the notions of weighted mean multigranulation decision-theoretic rough sets, optimistic multigranulation decision-theoretic rough sets, and pessimistic multigranulation decision-theoretic rough sets in an incomplete information system. We investigate the relationships between the proposed multigranulation decision-theoretic rough set models and other related rough set models. We also study some basic properties of these models. We give an example to illustrate the application of the proposed models.

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On an optimization representation of decision-theoretic rough set model

Cited by 123 publications

References 46 publications

A study on soft rough semigroups and corresponding decision making applications

A study on soft rough semigroups and corresponding decision making applications

An approach to emergency decision making based on decision-theoretic rough set over two universes

Multigranulation decision-theoretic rough sets in incomplete information systems

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