Theory and Applications of Problem Solving
Theory and Applications of Problem Solving
An axiomatic characterization of a fuzzy generalization of rough sets
Information Sciences—Informatics and Computer Science: An International Journal
Is there a need for fuzzy logic?
Information Sciences: an International Journal
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
MGRS: A multi-granulation rough set
Information Sciences: an International Journal
The structure analysis of fuzzy sets
International Journal of Approximate Reasoning
Decision-theoretic rough set models
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Positive approximation: An accelerator for attribute reduction in rough set theory
Artificial Intelligence
International Journal of Intelligent Systems
Comparison Of Rough-Set And Interval-Set Models For Uncertain Reasoning
Fundamenta Informaticae
Set-theoretic Approaches to Granular Computing
Fundamenta Informaticae - Rough Sets and Knowledge Technology (RSKT 2010)
Granular modelling of signals: A framework of Granular Computing
Information Sciences: an International Journal
Building the fundamentals of granular computing: A principle of justifiable granularity
Applied Soft Computing
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Humans have the innate ability to cope with and process incomplete and uncertain information. Any intelligent system should also have such an ability built in. Incomplete and uncertain information is formalized in different ways. By analyzing different methods for representing uncertain information, we propose a new method that uses a hierarchical coordinate to describe a total-order structure. This novel method describes information in different granular spaces by using hierarchical coordinates. The relationships among these spaces are constructed such that the transformation of information is possible. We extend the fuzzy equivalence and tolerance relations to weighted equivalence and tolerance relations, respectively. The properties of those relations and the isomorphism discriminant of information are described by using matrices. We develop a method for solving a complex problem with hierarchical coordinates. Simulation experiments demonstrate that a hierarchical coordinate system can help us to efficiently determine the optimal paths of large-scale networks.