You are not logged in.
Openly accessible

Can indices of ecological evenness be used to measure consensus?

Beliakov,G, James,S and Nimmo,D 2014, Can indices of ecological evenness be used to measure consensus?, in FUZZ-IEEE 2014 : Proceedings of the 2014 IEEE International Conference on Fuzzy Systems, IEEE, Piscataway, N.J., pp. 25-32, doi: 10.1109/FUZZ-IEEE.2014.6891596.

Attached Files
Name Description MIMEType Size Downloads
beliakov-canindices-post-2014.pdf Authors' post print application/pdf 1.03MB 23

Title Can indices of ecological evenness be used to measure consensus?
Author(s) Beliakov,GORCID iD for Beliakov,G orcid.org/0000-0002-9841-5292
James,SORCID iD for James,S orcid.org/0000-0003-1150-0628
Nimmo,D
Conference name IEEE International Conference on Fuzzy Systems (2014 : Beijing, China)
Conference location Beijing, China
Conference dates 6-11 Jul. 2014
Title of proceedings FUZZ-IEEE 2014 : Proceedings of the 2014 IEEE International Conference on Fuzzy Systems
Editor(s) [Unknown]
Publication date 2014
Conference series IEEE International Conference on Fuzzy Systems
Start page 25
End page 32
Total pages 8
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) aggregation functions
Consensus measures
decision making
ecological evenness
Summary In the context of group decision making with fuzzy preferences, consensus measures are employed to provide feedback and help guide automatic or semi-automatic decision reaching processes. These measures attempt to capture the intuitive notion of how much inputs, individuals or groups agree with one another. Meanwhile, in ecological studies there has been an ongoing research effort to define measures of community evenness based on how evenly the proportional abundances of species are distributed. The question hence arises as to whether there can be any cross-fertilization from developments in these fields given their intuitive similarity. Here we investigate some of the models used in ecology toward their potential use in measuring consensus. We found that although many consensus characteristics are exhibited by evenness indices, lack of reciprocity and a tendency towards a minimum when a single input is non-zero would make them undesirable for inputs expressed on an interval scale. On the other hand, we note that some of the general frameworks could still be useful for other types of inputs like ranking profiles and that in the opposite direction consensus measures have the potential to provide new insights in ecology.
ISBN 9781479920723
ISSN 1098-7584
Language eng
DOI 10.1109/FUZZ-IEEE.2014.6891596
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2014, Institute of Electrical and Electronics Engineers
Persistent URL http://hdl.handle.net/10536/DRO/DU:30069335

Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 1 times in TR Web of Science
Scopus Citation Count Cited 5 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 162 Abstract Views, 26 File Downloads  -  Detailed Statistics
Created: Mon, 02 Feb 2015, 12:17:42 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.