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Artificial Intelligence Review
Published in: Artificial Intelligence Review 3/2022

31-07-2021

Spherical fuzzy decision making method based on combined compromise solution for IIoT industry evaluation

Authors: Xindong Peng, Wenquan Li

Published in: Artificial Intelligence Review | Issue 3/2022

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Abstract

The Industrial Internet of Things is crucial for enterprise and country to drive the strategic upgrade and raise the level of national intelligent manufacturing. When pondering the IIoT industry evaluation, the corresponding dominating issues involve numerous indeterminacies. Spherical fuzzy set, portrayed by memberships of positive, neutral and negative, is a more efficient methods of seizing indeterminacy. In this article, firstly, the fire-new spherical fuzzy score function is explored for solving some suspensive comparison issues. Moreover, the objective weight and combined weight are determined by Renyi entropy method and non-linear weighted comprehensive method, respectively. Later, the multi-criteria decision making method based on combined compromise solutionis developed under spherical fuzzy environment. Finally, the corresponding method is effectively validated by the issue of IIoT industry evaluation. The main characteristics of the presented algorithm are: (1) without counterintuitive phenomena; (2) no division or antilogarithm by zero problem; (3) no square root by negative number issue; (4) no violation of the original definition issue.
previous article Updating approximations with dynamic objects based on local multigranulation rough sets in ordered information systems
next article An approach to MCGDM based on multi-granulation Pythagorean fuzzy rough set over two universes and its application to medical decision problem

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Metadata
Title
Spherical fuzzy decision making method based on combined compromise solution for IIoT industry evaluation
Authors
Xindong Peng
Wenquan Li
Publication date
31-07-2021
Publisher
Springer Netherlands
Published in
Artificial Intelligence Review / Issue 3/2022
Print ISSN: 0269-2821
Electronic ISSN: 1573-7462
DOI
https://doi.org/10.1007/s10462-021-10055-7

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