Bipolar-Valued Rough Fuzzy Set and Its Applications to the Decision Information System

Han, Ying; Shi, Peng; Chen, Sheng

doi:10.1109/tfuzz.2015.2423707

Cited by 62 publications

(19 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…These papers are cited as References [31][32][33]. We prove that the YinYang bipolar fuzzy set is not equivalent with the neutrosophic set, but a particular case of the bipolar neutrosophic set.…”

Section: Yinyang Bipolar Fuzzy Set Is the Bipolar Fuzzy Setmentioning

confidence: 97%

Refined Neutrosophy and Lattices vs. Pair Structures and YinYang Bipolar Fuzzy Set

Smarandache

2019

Mathematics

View full text Add to dashboard Cite

show abstract

Section: Yinyang Bipolar Fuzzy Set Is the Bipolar Fuzzy Setmentioning

confidence: 97%

Refined Neutrosophy and Lattices vs. Pair Structures and YinYang Bipolar Fuzzy Set

Smarandache

2019

Mathematics

View full text Add to dashboard Cite

show abstract

“…B p FSs contain two elements called, the positive membership degree (P v MD) and the negative membership degree (N v MD) to represent the bipolar fuzzy (B p F) information and the range both the degrees always lie in [−1, 1]. Currently, B p FSs have been utilized in various fields of research [7,9,[23][24][25]. Gul [5] presented several arithmetic and geometric operators for bipolar fuzzy information.…”

Section: Introductionmentioning

confidence: 99%

Multiple criteria decision making based on bipolar picture fuzzy sets and extended TOPSIS

Sindhu¹,

Ahsan²,

Rafiq³

et al. 2020

J. Math. Computer Sci.

View full text Add to dashboard Cite

The notion of bipolar fuzzy sets (B p FSs) has got much attention from the experts or decision-makers (DMs). B p FSs have ample information in the form of two degrees called the positive belonging degree (P v BD) and a negative belonging degree (N v BD). In this article, we introduced the concept of bipolar picture fuzzy sets (BP c FSs) by connecting the concepts of B p FSs and picture fuzzy sets (P c FSs). Firstly, we presented the concept, operational rules, score, and accuracy functions of BP c FSs. Secondly, a distance measure is formulated for the BP c FSs and then implemented for the extension of TOPSIS. Thirdly, a multiple criteria decision making (MCDM) model is proposed to handle the uncertain MCDM problems. Lastly, a practical example related to the sum of money's investment is exemplified to validate and effectiveness of the proposed model.

show abstract

“…But different from IFS, the value range of membership degree of the BFS is [−1, 1]. BFSs have been applied to logical reasoning and set theory [26], [27], Chinese medicine [28], [29], bipolar cognitive mapping [30], [31], computational psychiatry [32], [33], decision analysis and organizational modeling [34], [35], quantum computing [36] and [37], bio-systems regulation [28], [38], [39] and some other domains [36], [40]- [44]. Gul [45] proposed the bipolar fuzzy weighted and geometric aggregation operators.…”

Section: Introductionmentioning

confidence: 99%

MADM Method With Interval-Valued Bipolar Uncertain Linguistic Information for Evaluating the Computer Network Security

Gao

Wei

et al. 2019

IEEE Access

View full text Add to dashboard Cite

In this paper, we extend the traditional information aggregating operators to interval-valued bipolar uncertain linguistic sets (IVBULSs) and propose some interval-valued bipolar uncertain linguistic aggregating operators. Then, the good properties of these proposed operators are investigated and these operators are used to solve the interval-valued bipolar uncertain linguistic multiple attribute decision making (MADM) problems. An example for evaluating the computer network security is given to illustrate the proposed methodology. INDEX TERMS Multiple attribute decision making (MADM), bipolar fuzzy sets (BFSs), interval-valued bipolar uncertain linguistic sets (IVBULSs), interval-valued bipolar uncertain linguistic hybrid average (IVBULHA) operator, interval-valued bipolar uncertain linguistic hybrid geometric (IVBULHG) operator, computer network security.

show abstract

Bipolar-Valued Rough Fuzzy Set and Its Applications to the Decision Information System

Cited by 62 publications

References 28 publications

Refined Neutrosophy and Lattices vs. Pair Structures and YinYang Bipolar Fuzzy Set

Refined Neutrosophy and Lattices vs. Pair Structures and YinYang Bipolar Fuzzy Set

Multiple criteria decision making based on bipolar picture fuzzy sets and extended TOPSIS

MADM Method With Interval-Valued Bipolar Uncertain Linguistic Information for Evaluating the Computer Network Security

Contact Info

Product

Resources

About