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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 2/2015

01.02.2015 | Original Article

The generalized hybrid weighted average operator based on interval neutrosophic hesitant set and its application to multiple attribute decision making

verfasst von: Peide Liu, Lanlan Shi

Erschienen in: Neural Computing and Applications | Ausgabe 2/2015

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Abstract

The Neutrosophic set and Hesitant set are the important and effective tools to describe the uncertain information. In this paper, we combine the interval neutrosophic sets and interval-valued hesitant fuzzy sets, and propose the concept of the interval neutrosophic hesitant fuzzy set (INHFS) in order to use the advantages of them. Then, we present the operations and comparison method of INHFS, and develop some new aggregation operators for the interval neutrosophic hesitant fuzzy information, including interval neutrosophic hesitant fuzzy generalized weighted operator, interval neutrosophic hesitant fuzzy generalized ordered weighted operator, and interval neutrosophic hesitant fuzzy generalized hybrid weighted operator, and discuss some properties. Furthermore, we propose the decision-making method for multiple attribute group decision making with interval neutrosophic hesitant fuzzy information, and give the detail decision steps. Finally, we give an illustrate example to show the process of decision making.
Vorheriger Artikel Stochastic stability analysis for neural networks with mixed time-varying delays
Nächster Artikel Affect-insensitive speaker recognition systems via emotional speech clustering using prosodic features

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Metadaten
Titel
The generalized hybrid weighted average operator based on interval neutrosophic hesitant set and its application to multiple attribute decision making
verfasst von
Peide Liu
Lanlan Shi
Publikationsdatum
01.02.2015
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 2/2015
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-014-1736-4

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