Proceedings of the 2015 International Conference on Management, Education, Information and Control

Theoretical Research on Granular Computing and Artificial Selection Algorithm

Authors
Shoubai Xiao
Corresponding Author
Shoubai Xiao
Available Online June 2015.
DOI
https://doi.org/10.2991/meici-15.2015.118How to use a DOI?
Keywords
Rough set; Granular computing; Binary granular matrix; Rough relationship matrix, Artificial Selection Algorithm.
Abstract
Today, with the rapid development of science and technology, knowledge and wisdom play greater roles and the evolution of artifacts is faster. The speed of artificial evolution cannot be followed by natural evolution. As a kind of new intelligent information processing technology, granular computing enjoys widespread concern of scholars. The constant integration of biological evolution, artificial life and calculation method has also been a hot research topic among scholars. The main findings of this paper include the following four parts: propose Rough set model based on granular computing; propose knowledge discovery algorithm based on granular computing; propose new project modeling method based on granular computing; propose Artificial Selection Algorithm (ASA) based on granular computing. This paper unifies the existing classic Rough set model, Rough set model based on probability and Rough set model based on inclusion degree all on the Rough set model based on granular computing.
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Proceedings
2015 International Conference on Management, Education, Information and Control
Part of series
Advances in Intelligent Systems Research
Publication Date
June 2015
ISBN
978-94-62520-85-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/meici-15.2015.118How 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  - Shoubai Xiao
PY  - 2015/06
DA  - 2015/06
TI  - Theoretical Research on Granular Computing and Artificial Selection Algorithm
BT  - 2015 International Conference on Management, Education, Information and Control
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-15.2015.118
DO  - https://doi.org/10.2991/meici-15.2015.118
ID  - Xiao2015/06
ER  -