A generalization of the Bonferroni mean based on partitions
Contribuinte(s) |
[Unknown] |
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Data(s) |
01/01/2013
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Resumo |
The mean defined by Bonferroni in 1950 (known by the same name) averages all non-identical product pairs of the inputs. Its generalizations to date have been able to capture unique behavior that may be desired in some decision-making contexts such as the ability to model mandatory requirements. In this paper, we propose a composition that averages conjunctions between the respective means of a designated subset-size partition. We investigate the behavior of such a function and note the relationship within a given family as the subset size is changed. We found that the proposed function is able to more intuitively handle multiple mandatory requirements or mandatory input sets. |
Identificador | |
Idioma(s) |
eng |
Publicador |
IEEE Computational Intelligence Society |
Relação |
http://dro.deakin.edu.au/eserv/DU:30060732/beliakov-ageneralization-post-2013.pdf http://dro.deakin.edu.au/eserv/DU:30060732/beliakov-generalizationofthe-2013.pdf http://dro.deakin.edu.au/eserv/DU:30060732/beliakov-generalizationofthe-evid-2013.pdf http://dro.deakin.edu.au/eserv/DU:30060732/reasonforpostprint.pdf http://doi.org/10.1109/FUZZ-IEEE.2013.6622348 |
Direitos |
2013, IEEE |
Palavras-Chave | #aggregation functions #bonferroni mean #decision making #mandatory criteria |
Tipo |
Conference Paper |