Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)

Fuzzy logic-predicate network

Authors
Tatiana Kosovskaia
Corresponding Author
Tatiana Kosovskaia
Available Online August 2019.
DOI
10.2991/eusflat-19.2019.2How to use a DOI?
Keywords
hierarchical description logic-predicate recognition network fuzzy recognition
Abstract

In many Artificial Intelligence problems an investigated object is considered as a set of its elements {ω1,...,ωt} and is characterized by properties of these elements and relations between them. These properties and relations may be set by predicates p1,..., pn. The problems appeared with such an approach become to be NP-complete or NP-hard ones. To decrease the computational complexity of these problems a hierarсhical many-level description of classes was suggested. A logic-predicate recognition network may be constructed according to such a many-level description. Such a network recognizes only objects which have been in the training set, but it may be easily retrained by a new object. After retraining it may change its configuration, i.e. the number of levels and the number of nodes in every level. A modification of such a network is offered in this paper. This modification allows to do a fuzzy recognition of a new object and to calculate the degree of certainty that this object or its part belongs to some class of objects.

Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)
Series
Atlantis Studies in Uncertainty Modelling
Publication Date
August 2019
ISBN
10.2991/eusflat-19.2019.2
ISSN
2589-6644
DOI
10.2991/eusflat-19.2019.2How to use a DOI?
Copyright
© 2019, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Tatiana Kosovskaia
PY  - 2019/08
DA  - 2019/08
TI  - Fuzzy logic-predicate network
BT  - Proceedings of the 11th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT 2019)
PB  - Atlantis Press
SP  - 9
EP  - 13
SN  - 2589-6644
UR  - https://doi.org/10.2991/eusflat-19.2019.2
DO  - 10.2991/eusflat-19.2019.2
ID  - Kosovskaia2019/08
ER  -