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Neural Computing and Applications

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01.12.2014 | Original Article

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

verfasst von: Peide Liu, Yumei Wang

Erschienen in: Neural Computing and Applications | Ausgabe 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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Titel: Multiple attribute decision-making method based on single-valued neutrosophic normalized weighted Bonferroni mean
verfasst von: Peide Liu
Yumei Wang
Publikationsdatum: 01.12.2014
Verlag: Springer London
Erschienen in: Neural Computing and Applications / Ausgabe 7-8/2014
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-014-1688-8

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