No Cover Image

Journal article 457 views

Type-1 OWA operators for aggregating uncertain information with uncertain weights induced by type-2 linguistic quantifiers / Shang-ming, Zhou

Fuzzy Sets and Systems, Volume: 159, Issue: 24, Pages: 3281 - 3296

Swansea University Author: Shang-ming, Zhou

Full text not available from this repository: check for access using links below.

Abstract

The OWA operator proposed by Yager has been widely used to aggregate experts’ opinions or preferences in human decision making. Yager's traditional OWA operator focuses exclusively on the aggregation of crisp numbers. However, experts usually tend to express their opinions or preferences in...

Full description

Published in: Fuzzy Sets and Systems
ISSN: 01650114
Published: 2008
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa10069
Tags: Add Tag
No Tags, Be the first to tag this record!
Abstract: The OWA operator proposed by Yager has been widely used to aggregate experts’ opinions or preferences in human decision making. Yager's traditional OWA operator focuses exclusively on the aggregation of crisp numbers. However, experts usually tend to express their opinions or preferences in a very natural way via linguistic terms. These linguistic terms can be modelled or expressed by (type-1) fuzzy sets. In this paper, we define a new type of OWA operator, the type-1 OWA operator that works as an uncertain OWA operator to aggregate type-1 fuzzy sets with type-1 fuzzy weights, which can be used to aggregate the linguistic opinions or preferences in human decision making with linguistic weights. The procedure for performing type-1 OWA operations is analysed. In order to identify the linguistic weights associated to the type-1 OWA operator, type-2 linguistic quantifiers are proposed. The problem of how to derive linguistic weights used in type-1 OWA aggregation given such type of quantifier is solved. Examples are provided to illustrate the proposed concepts.
College: Swansea University Medical School
Issue: 24
Start Page: 3281
End Page: 3296