@INPROCEEDINGS { Rsds4863,
author = {Zeng, Huanglin and Zeng, Xiaohui}, 
title = {Reasoning Decision Rules of an Uncertain System}, 
booktitle = {Rough Sets and Knowledge Technology}, 
conference = {Rough Sets and Knowledge Technology}, 
series =  = {Lecture Notes in Artificial Intelligence}, 
volume = 5589, 
pages = {634--641}, 
publisher = {Springer-Verlag}, 
address = {Heidelberg - Berlin, Germany}, 
month = {July}, 
year = 2009, 
editor = {Wen, Peng and Li, Yuefeng and Polkowski, Lech and Yao, Yiyu and Tsumoto, Shusaku and Wang, Guoying}, 
url = {http://www.springerlink.com/content/q0857121u072/?p=fc4581dabf904891bbe1f9cc3f4fdd0d&pi=313}, 
issn = {0302-9743}, 
isbn = {978-3-642-02961-5}, 
abstract = {This paper is devoted to some studies in reasoning decision rules of an uncertain information system which is an incomplete or imprecise even ill-defined database. At first, Theoretical aspects of the knowledge redundancy and the knowledge simplification of an uncertain system is discussed based on theoretical aspects of rough sets. A maximal information coverage rate is defined with the acquired data of a decision table in an information system on condition attributes. A criterion of the knowledge simplification and a basic algorithm realization of reasoning decision rules of an uncertain information system is presented to induce a mathematical model of an uncertain system with the maximum information coverage. The feasibility of the proposed approach of reasoning decision rules is validated by some of examples here.}, 
keywords = {an uncertain information system, data mining, information coverage, rough sets, statistical methods, decision rules, }, 
}