A fuzzy rough set approach to emergency material demand prediction over two universes

Sun, Baiqing; Ma, Weimin; Zhao, Haiyan

doi:10.1016/j.apm.2013.02.008

Cited by 69 publications

(57 citation statements)

References 23 publications

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“…which are in accordance with the definition of (type-1) fuzzy rough set over two universes given in [29]. Example 1.…”

Section: Type-2 Fuzzy Rough Sets Over Two Universessupporting

confidence: 57%

“…is the most seriously affected areas; if T 1 ∩ T 2 = ∅, we take x i (i ∈ T 2 ) as the most seriously affected areas [29].…”

Section: R(x Imentioning

confidence: 99%

“…Ma et al [28] presented the properties of the probabilistic rough set over two universes and discussed the uncertainty measure of the knowledge granularity and rough entropy for a probabilistic rough set over two universes. Sun et al [29] considered a problem of emergency material demand prediction based on a fuzzy rough set model over two universes. Yang et al proposed a fuzzy probabilistic rough set model on two universes and presented concepts of the inverse lower and upper approximation operators in [30].…”

Section: Introductionmentioning

confidence: 99%

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Granular Structure of Type-2 Fuzzy Rough Sets over Two Universes

Lü

Zhai

et al. 2017

Symmetry

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Granular structure plays a very important role in the model construction, theoretical analysis and algorithm design of a granular computing method. The granular structures of classical rough sets and fuzzy rough sets have been proven to be clear. In classical rough set theory, equivalence classes are basic granules, and the lower and upper approximations of a set can be computed by those basic granules. In the theory of fuzzy rough set, granular fuzzy sets can be used to describe the lower and upper approximations of a fuzzy set. This paper discusses the granular structure of type-2 fuzzy rough sets over two universes. Definitions of type-2 fuzzy rough sets over two universes are given based on a wavy-slice representation of type-2 fuzzy sets. Two granular type-2 fuzzy sets are deduced and then proven to be basic granules of type-2 fuzzy rough sets over two universes. Then, the properties of lower and upper approximation operators and these two granular type-2 fuzzy sets are investigated. At last, several examples are given to show the applications of type-2 fuzzy rough sets over two universes.

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“…which are in accordance with the definition of (type-1) fuzzy rough set over two universes given in [29]. Example 1.…”

Section: Type-2 Fuzzy Rough Sets Over Two Universessupporting

confidence: 57%

“…is the most seriously affected areas; if T 1 ∩ T 2 = ∅, we take x i (i ∈ T 2 ) as the most seriously affected areas [29].…”

Section: R(x Imentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Granular Structure of Type-2 Fuzzy Rough Sets over Two Universes

Lü

Zhai

et al. 2017

Symmetry

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“…Feng et al [34] investigated reduction of the multigranulation fuzzy information system based on uncertainty measures by considering variable precision multigranulation decisiontheoretic fuzzy-rough set theory and avoiding the changing of negative region and positive region to small ones. Sun et al [62] proposed the new fuzzy-rough set on a probabilistic approximation space and used it with respect to decisionmaking in unconventional emergency management. Hu et al [171] proposed a new incremental method to update approximations of fuzzy information system over two universes.…”

Section: Related Workmentioning

confidence: 99%

Recent Fuzzy Generalisations of Rough Sets Theory: A Systematic Review and Methodological Critique of the Literature

et al. 2017

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Rough set theory has been used extensively in fields of complexity, cognitive sciences, and artificial intelligence, especially in numerous fields such as expert systems, knowledge discovery, information system, inductive reasoning, intelligent systems, data mining, pattern recognition, decision-making, and machine learning. Rough sets models, which have been recently proposed, are developed applying the different fuzzy generalisations. Currently, there is not a systematic literature review and classification of these new generalisations about rough set models. Therefore, in this review study, the attempt is made to provide a comprehensive systematic review of methodologies and applications of recent generalisations discussed in the area of fuzzy-rough set theory. On this subject, the Web of Science database has been chosen to select the relevant papers. Accordingly, the systematic and metaanalysis approach, which is called "PRISMA," has been proposed and the selected articles were classified based on the author and year of publication, author nationalities, application field, type of study, study category, study contribution, and journal in which the articles have appeared. Based on the results of this review, we found that there are many challenging issues related to the different application area of fuzzy-rough set theory which can motivate future research studies.

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“…Hence, Pei and Xu [26] studied the concept of rough sets over two universes systematically. Since then, several scholars have researched rough sets over two universes widely according to numerous practical requirements [27][28][29][30][31][32][33]. Recently, in order to expand the application scopes of rough sets over two universes from the ideas of granular computing, Sun and Ma [34] introduced multigranulation rough sets over two universes, which could not only describe real-life decision making information effectively and reasonably through different universes of discourse, but also integrate each expert's opinion to form an ultimate conclusion by aggregating multiple binary relations.…”

mentioning

confidence: 99%

Merger and Acquisition Target Selection Based on Interval Neutrosophic Multigranulation Rough Sets over Two Universes

Zhang

Sangaiah

2017

Symmetry

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Abstract:As a significant business activity, merger and acquisition (M&A) generally means transactions in which the ownership of companies, other business organizations or their operating units are transferred or combined. In a typical M&A procedure, M&A target selection is an important issue that tends to exert an increasingly significant impact on different business areas. Although some research works based on fuzzy methods have been explored on this issue, they can only deal with incomplete and uncertain information, but not inconsistent and indeterminate information that exists universally in the decision making process. Additionally, it is advantageous to solve M&A problems under the group decision making context. In order to handle these difficulties in M&A target selection background, we introduce a novel rough set model by combining interval neutrosophic sets (INSs) with multigranulation rough sets over two universes, called an interval neutrosophic (IN) multigranulation rough set over two universes. Then, we discuss the definition and some fundamental properties of the proposed model. Finally, we establish decision making rules and computing approaches for the proposed model in M&A target selection background, and the effectiveness of the decision making approach is demonstrated by an illustrative case analysis.

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A fuzzy rough set approach to emergency material demand prediction over two universes

Cited by 69 publications

References 23 publications

Granular Structure of Type-2 Fuzzy Rough Sets over Two Universes

Granular Structure of Type-2 Fuzzy Rough Sets over Two Universes

Recent Fuzzy Generalisations of Rough Sets Theory: A Systematic Review and Methodological Critique of the Literature

Merger and Acquisition Target Selection Based on Interval Neutrosophic Multigranulation Rough Sets over Two Universes

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