Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Redundant data processing based on rough-fuzzy approach
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Comprehensive evaluation of chinese liquor quality based on improved gray-clustering analysis
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part II
| Hi-index | 0.00 |
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.