Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Generalized Decision Algorithms, Rough Inference Rules, and Flow Graphs
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
First Course On Fuzzy Theory And Applications.
First Course On Fuzzy Theory And Applications.
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
The computational complexity of inference using rough set flow graphs
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Transactions on Rough Sets III
Novel matrix forms of rough set flow graphs with applications to data integration
Computers & Mathematics with Applications
An extension of rough set approximation to flow graph based data analysis
RSCTC'10 Proceedings of the 7th international conference on Rough sets and current trends in computing
Adaptive Method of Adjusting Flowgraph for Route Reconstruction in Video Surveillance Systems
Fundamenta Informaticae - To Andrzej Skowron on His 70th Birthday
Ant-Based Clustering in Delta Episode Information Systems Based on Temporal Rough Set Flow Graphs
Fundamenta Informaticae - Concurrency, Specification and Programming
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The paper makes the first attempt to combine two methodologiesconcerning uncertainty and fuzzy reasoning, namely rough set flowgraphs and fuzzy relation equations. Rough set flow graphs proposedby Z. Pawlak are a useful tool for the knowledge representation. Inthis paper, we use them to represent the knowledge of transitionsbetween states included in multistage dynamic information systems.The knowledge represented by flow graphs is a basis for determiningpossibilities of appearances of states in the future using themax- * fuzzy composition. In the approach proposed in thepaper, we take advantage of some properties of the max- *fuzzy relation equations.