International Journal of Computational Intelligence Systems

Volume 8, Issue 6, December 2015, Pages 1027 - 1043

An Improved Weighted Correlation Coefficient Based on Integrated Weight for Interval Neutrosophic Sets and its Application in Multi-criteria Decision-making Problems

Authors
Hong-yu Zhang, Pu Ji, Jian-qiang Wang, Xiao-hong Chen
Corresponding Author
Jian-qiang Wang
Received 7 January 2015, Accepted 24 August 2015, Available Online 1 December 2015.
DOI
10.1080/18756891.2015.1099917How to use a DOI?
Keywords
Interval neutrosophic sets, objective weight, integrated weight, correlation coefficient, multi-criteria decision-making
Abstract

This paper presents a new correlation coefficient measure, which satisfies the requirement of this measure equaling one if and only if two interval neutrosophic sets (INSs) are the same. And an objective weight of INSs is presented to unearth and utilize deeper information that is uncertain. Using the proposed weighted correlation coefficient measure of INSs, a decision-making method is developed, which takes into account the influence of the evaluations’ uncertainty and both the objective and subjective weights.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
8 - 6
Pages
1027 - 1043
Publication Date
2015/12/01
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.1080/18756891.2015.1099917How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - Hong-yu Zhang
AU  - Pu Ji
AU  - Jian-qiang Wang
AU  - Xiao-hong Chen
PY  - 2015
DA  - 2015/12/01
TI  - An Improved Weighted Correlation Coefficient Based on Integrated Weight for Interval Neutrosophic Sets and its Application in Multi-criteria Decision-making Problems
JO  - International Journal of Computational Intelligence Systems
SP  - 1027
EP  - 1043
VL  - 8
IS  - 6
SN  - 1875-6883
UR  - https://doi.org/10.1080/18756891.2015.1099917
DO  - 10.1080/18756891.2015.1099917
ID  - Zhang2015
ER  -