Research on the Approach of Knowledge Acquisition in Expert Systems based on Rough Sets Theory

DOI

10.2991/icecee-15.2015.235How to use a DOI?

Keywords

Expert Systems; Rough Sets; Knowledge Discovery; Data Mining; Artificial Intelligence

Abstract

The research on expert systems has been a hotspot. In order to resolve the problems about knowledge acquisition in complete and incomplete knowledge representation systems, the algorithm of knowledge acquisition based on rough set theory is proposed. Let the knowledge representation system be a decision table, the useful knowledge can be obtained by simplification of the decision table. The algorithm of computation of condition attributes’ reductions and the algorithm of computation of reduction of decision rule are researched to simplify the decision table. When there are missing values in knowledge representation systems, the missing data should be completed by the algorithm of missing values’ completion firstly. This algorithm of knowledge acquisition based on rough set theory can obtain a minimal set of decision rules which can be used to reason in expert systems. The approach of knowledge acquisition can be used to simplify uncertain and incomplete knowledge representation systems.

Copyright

© 2015, 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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TY  - CONF
AU  - Yehong Han
PY  - 2015/06
DA  - 2015/06
TI  - Research on the Approach of Knowledge Acquisition in Expert Systems based on Rough Sets Theory
BT  - Proceedings of the 2015 International Conference on Electrical, Computer Engineering and Electronics
PB  - Atlantis Press
SP  - 1265
EP  - 1270
SN  - 2352-538X
UR  - https://doi.org/10.2991/icecee-15.2015.235
DO  - 10.2991/icecee-15.2015.235
ID  - Han2015/06
ER  -