Proceedings of the 2016 International Conference on Electrical, Mechanical and Industrial Engineering

Grey Ontology Model for Expert Knowledge Representation

Authors
Bin Shen, Shuyu Zhao
Corresponding Author
Bin Shen
Available Online April 2016.
DOI
10.2991/icemie-16.2016.41How to use a DOI?
Keywords
ontology; grey number; knowledge representation; expert knownledge
Abstract

In order to improve the knowledge representation of ontology for dealing with grey uncertainty, grey ontology is proposed. Firstly, grey systems theory, probability theory and fuzzy theory are compared. Secondly, interval grey number and its calculation are introduced. At last, the model grey ontology is proposed and the main elements are also analyzed. It shows that grey ontology can overcome the limitation of other ontologies to describe the expert knowledge with grey uncertainty.

Copyright
© 2016, 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 2016 International Conference on Electrical, Mechanical and Industrial Engineering
Series
Advances in Engineering Research
Publication Date
April 2016
ISBN
978-94-6252-182-7
ISSN
2352-5401
DOI
10.2991/icemie-16.2016.41How to use a DOI?
Copyright
© 2016, 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  - Bin Shen
AU  - Shuyu Zhao
PY  - 2016/04
DA  - 2016/04
TI  - Grey Ontology Model for Expert Knowledge Representation
BT  - Proceedings of the 2016 International Conference on Electrical, Mechanical and Industrial Engineering
PB  - Atlantis Press
SP  - 165
EP  - 168
SN  - 2352-5401
UR  - https://doi.org/10.2991/icemie-16.2016.41
DO  - 10.2991/icemie-16.2016.41
ID  - Shen2016/04
ER  -