Next Article in Journal
Analysis of Robot Selection Based on 2-Tuple Picture Fuzzy Linguistic Aggregation Operators
Next Article in Special Issue
Evaluating the Suitability of a Smart Technology Application for Fall Detection Using a Fuzzy Collaborative Intelligence Approach
Previous Article in Journal
Bureaucratic Reshuffling and Efficiency: Do n-Competing Bureaus Determine Inefficient Results?
Previous Article in Special Issue
Fuzzy Multicriteria Decision-Making Model (MCDM) for Raw Materials Supplier Selection in Plastics Industry
Open AccessArticle

A Multi-Attribute Pearson’s Picture Fuzzy Correlation-Based Decision-Making Method

1
College of Economic and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
2
College of Big Data and Software Engineering, Zhejiang Wanli University, Ningbo 315100, China
3
College of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China
4
School of Business, Ningbo University, Ningbo 315211, China
5
School of Management, Nanchang University, Nanchang 330031, China
*
Authors to whom correspondence should be addressed.
Mathematics 2019, 7(10), 999; https://doi.org/10.3390/math7100999
Received: 1 August 2019 / Revised: 11 October 2019 / Accepted: 16 October 2019 / Published: 21 October 2019
(This article belongs to the Special Issue Operations Research Using Fuzzy Sets Theory)
As a generalization of several fuzzy tools, picture fuzzy sets (PFSs) hold a special ability to perfectly portray inherent uncertain and vague decision preferences. The intention of this paper is to present a Pearson’s picture fuzzy correlation-based model for multi-attribute decision-making (MADM) analysis. To this end, we develop a new correlation coefficient for picture fuzzy sets, based on which a Pearson’s picture fuzzy closeness index is introduced to simultaneously calculate the relative proximity to the positive ideal point and the relative distance from the negative ideal point. On the basis of the presented concepts, a Pearson’s correlation-based model is further presented to address picture fuzzy MADM problems. Finally, an illustrative example is provided to examine the usefulness and feasibility of the proposed methodology. View Full-Text
Keywords: picture fuzzy sets; multi-attribute decision-making; correlation-based closeness index; Pearson’s correlation picture fuzzy sets; multi-attribute decision-making; correlation-based closeness index; Pearson’s correlation
MDPI and ACS Style

Jin, Y.; Wu, H.; Sun, D.; Zeng, S.; Luo, D.; Peng, B. A Multi-Attribute Pearson’s Picture Fuzzy Correlation-Based Decision-Making Method. Mathematics 2019, 7, 999.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop