Some Remarks on the Concept of Approximations from the View of Knowledge Engineering

Authors:
Tsau Young Lin;Rushin Barot;Shusaku Tsumoto
Affiliations:
San Jose State University, USA;San Jose State University, USA;Shimane Medical University, Japan
Venue:
International Journal of Cognitive Informatics and Natural Intelligence
Year:
2010

Citing 3
Cited 2

Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic

Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
The 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings

ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
A roadmap from rough set theory to granular computing

RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology

Relationships among generalized rough sets in six coverings and pure reflexive neighborhood system

Information Sciences: an International Journal
Unifying Rough Set Theories via Large Scaled Granular Computing

Fundamenta Informaticae - To Andrzej Skowron on His 70th Birthday

Quantified Score

Hi-index	0.00

Visualization

Abstract

The concepts of approximations in granular computing GrC vs. rough set theory RS are examined. Examples are constructed to contrast their differences in the Global GrC Model 2nd GrC Model, which, in pre-GrC term, is called partial coverings. Mathematically speaking, RS-approximations are "sub-base" based, while GrC-approximations are "base" based, where "sub-base" and "base" are two concepts in topological spaces. From the view of knowledge engineering, its meaning in RS-approximations is rather obscure, while in GrC, it is the concept of knowledge approximations.