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Neural Computing and Applications
Published in: Neural Computing and Applications 7-8/2014

01-12-2014 | Original Article

Multiple attribute decision-making method based on single-valued neutrosophic normalized weighted Bonferroni mean

Authors: Peide Liu, Yumei Wang

Published in: Neural Computing and Applications | Issue 7-8/2014

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Abstract

In this paper, we proposed a single-valued neutrosophic normalized weighted Bonferroni mean (SVNNWBM) operator on the basis of Bonferroni mean, the weighted Bonferroni mean (WBM), and the normalized WBM. Firstly, the definition, operational laws, characteristics, and comparing method of single-valued neutrosophic numbers (SVNNs) are introduced. Then, the SVNNWBM operator is developed, and some properties and special cases of this operator are analyzed. Furthermore, an approach is developed to solve the multiple attribute decision-making problems with SVNNs based on the SVNNWBM operator. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.
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Metadata
Title
Multiple attribute decision-making method based on single-valued neutrosophic normalized weighted Bonferroni mean
Authors
Peide Liu
Yumei Wang
Publication date
01-12-2014
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 7-8/2014
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-014-1688-8

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