Universal approximation using radial-basis-function networks
Neural Computation
Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Neighborhood systems and relational databases
CSC '88 Proceedings of the 1988 ACM sixteenth annual conference on Computer science
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Data Mining and Machine Oriented Modeling: A Granular Computing Approach
Applied Intelligence
Logics Systems for Approximate Reasoning: Approximation via Rough Sets and Topological Spaces
ISMIS '94 Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems
Rough Approximate Operators: Axiomatic Rough Set Theory
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Topological data models and approximate retrieval and reasoning
CSC '89 Proceedings of the 17th conference on ACM Annual Computer Science Conference
Uncertainty Measure of Covering Generated Rough Set
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
Design of nearest neighbor classifiers: multi-objective approach
International Journal of Approximate Reasoning
Granular computing: structures, representations, and applications
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Pattern classification using class-dependent rough-fuzzy granular space
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Diverse reduct subspaces based co-training for partially labeled data
International Journal of Approximate Reasoning
Rough-wavelet granular space and classification of multispectral remote sensing image
Applied Soft Computing
Class-dependent rough-fuzzy granular space, dispersion index and classification
Pattern Recognition
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"Nearest" neighborhoods are informally used in many areas of AI and database. Mathematically, a "nearest" neighborhood system that maps each object p a unique crisp/fuzzy subset of data, representing the "nearest" neighborhood, is a binary relation between the object and data spaces. "Nearest" neighborhood consists of data that are semantically related to p, and represents an elementary granule(atoms) of the system under consideration. This paper examines "rough set theory" of these elementary granules. Applications to databases, fuzzy sets and pattern recognition are used to illustrate the idea.