Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-11)

Membership-based clustering of heterogeneous fuzzy data

Authors
Gernot Herbst, Arne-Jens Hempel, Rainer Fletling, Steffen F. Bocklisch
Corresponding Author
Gernot Herbst
Available Online August 2011.
DOI
https://doi.org/10.2991/eusflat.2011.119How to use a DOI?
Keywords
Fuzzy classification, clustering, pattern recognition, engineering geodesy.
Abstract
This article contributes to clustering and fuzzy modelling of data such that specific characteristics of each datum can be incorporated. Particularly, each object may exhibit an individual area of influence in its feature space, for which it is representative. For such objects, a similarity measure is introduced, which is used to modify common clustering algorithms to take each object's extent into account when finding clusters. A real-world example demonstrates the practical usability of the presented methods, which deliver results in accordance to findings of experts in that field.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology
Part of series
Advances in Intelligent Systems Research
Publication Date
August 2011
ISBN
978-90-78677-00-0
DOI
https://doi.org/10.2991/eusflat.2011.119How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Gernot Herbst
AU  - Arne-Jens Hempel
AU  - Rainer Fletling
AU  - Steffen F. Bocklisch
PY  - 2011/08
DA  - 2011/08
TI  - Membership-based clustering of heterogeneous fuzzy data
BT  - Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology
PB  - Atlantis Press
SP  - 283
EP  - 289
UR  - https://doi.org/10.2991/eusflat.2011.119
DO  - https://doi.org/10.2991/eusflat.2011.119
ID  - Herbst2011/08
ER  -