Journal
KNOWLEDGE-BASED SYSTEMS
Volume 84, Issue -, Pages 134-143Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2015.04.008
Keywords
Hesitant fuzzy set; Membership uncertainty; Aggregation principle; Aggregation operator
Categories
Funding
- MOE Project of Humanities and Social Sciences [14YJC910006]
- Zhejiang Province Natural Science Foundation [LQ14G010002]
- Statistical Scientific Key Research Project of China [2013LZ48]
- Key Research Center of Philosophy and Social Science of Zhejiang Province Modern Port Service Industry and Creative Culture Research Center
- Projects in Science and Technique of Ningbo Municipal [2012B82003]
Ask authors/readers for more resources
In this paper, we present and apply a new aggregation principle for hesitant fuzzy elements (HFEs). First, we introduce a membership uncertainty index of the HFEs. Then we present a new aggregation principle for aggregating hesitant fuzzy elements, which can effectively reduce the computational complexity specific to the conventional aggregation principle. By the virtue of the proposed aggregation principle, the number of terms (values) in the aggregation result is significantly reduced. Furthermore, a t-test confirms that the scores associated with the results of the aggregation under conventional and new principles have no significant difference. Finally, a series of simulations are provided to demonstrate the feasibility and validity of the proposed aggregation principle. (C) 2015 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available