Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/136280
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Alfaro-García, Víctor G. | - |
dc.contributor.author | Merigó Lindahl, José M. | - |
dc.contributor.author | Gil Lafuente, Anna Maria | - |
dc.contributor.author | Kacprzyk, Janusz | - |
dc.date.accessioned | 2019-07-02T09:20:19Z | - |
dc.date.available | 2019-07-31T05:10:17Z | - |
dc.date.issued | 2018-07 | - |
dc.identifier.issn | 0884-8173 | - |
dc.identifier.uri | http://hdl.handle.net/2445/136280 | - |
dc.description.abstract | The Hamming distance is a well‐known measure that is designed to provide insights into the similarity between two strings of information. In this study, we use the Hamming distance, the optimal deviation model, and the generalized ordered weighted logarithmic averaging (GOWLA) operator to develop the ordered weighted logarithmic averaging distance (OWLAD) operator and the generalized ordered weighted logarithmic averaging distance (GOWLAD) operator. The main advantage of these operators is the possibility of modeling a wider range of complex representations of problems under the assumption of an ideal possibility. We study the main properties, alternative formulations, and families of the proposed operators. We analyze multiple classical measures to characterize the weighting vector and propose alternatives to deal with the logarithmic properties of the operators. Furthermore, we present generalizations of the operators, which are obtained by studying their weighting vectors and the lambda parameter. Finally, an illustrative example regarding innovation project management measurement is proposed, in which a multi‐expert analysis and several of the newly introduced operators are utilized. | - |
dc.format.extent | 19 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Wiley | - |
dc.relation.isformatof | Versió postprint del document publicat a: https://doi.org/10.1002/int.21988 | - |
dc.relation.ispartof | International Journal of Intelligent Systems, 2018, vol. 33, num. 7, p. 1488-1506 | - |
dc.relation.uri | https://doi.org/10.1002/int.21988 | - |
dc.rights | (c) Wiley, 2018 | - |
dc.source | Articles publicats en revistes (Empresa) | - |
dc.subject.classification | Logaritmes | - |
dc.subject.classification | Mesurament de les distàncies | - |
dc.subject.classification | Teoria d'operadors | - |
dc.subject.other | Logarithms | - |
dc.subject.other | Measurement of distances | - |
dc.subject.other | Operator theory | - |
dc.title | Logarithmic aggregation operators and distance measures | - |
dc.type | info:eu-repo/semantics/article | - |
dc.type | info:eu-repo/semantics/acceptedVersion | - |
dc.identifier.idgrec | 679562 | - |
dc.date.updated | 2019-07-02T09:20:19Z | - |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
Appears in Collections: | Articles publicats en revistes (Empresa) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
679562.pdf | 340.4 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.