Beschreibung
InhaltsangabePart I Theoretical Contributions to Rough Set Theory.- Rough Sets on Fuzzy Approximation Spaces and Intuitionistic Fuzzy Approximation Spaces.- Categorical Innovations for Rough Sets.- Granular Structures and Approximations in Rough Sets and Knowledge Spaces.- On Approximation of Classifications, Rough Equalities and Rough Equivalences.- Part II Rough Set Data Mining Activities.- Rough Clustering with Partial Supervision.- A Generic Scheme for Generating Prediction Rules Using Rough Sets.- Rough Web Caching.- Software Defect Classification: A Comparative Study of Rough-Neuro-Fuzzy Hybrid Approaches with Linear and Non-Linear SVMs.- Part III Rough Hybrid Models to Classification and Attribute Reduction.- Rough Sets and Evolutionary Computation to Solve the Feature Selection Problem.- Nature Inspired Population-based Heuristics for Rough Set Reduction.- Developing a Knowledge-based System using Rough Set Theory and Genetic Algorithms for Substation Fault Diagnosis.
Inhalt
Part I Theoretical Contributions to Rough Set Theory.- Rough Sets on Fuzzy Approximation Spaces and Intuitionistic Fuzzy Approximation Spaces.- Categorical Innovations for Rough Sets.- Granular Structures and Approximations in Rough Sets and Knowledge Spaces.- On Approximation of Classifications, Rough Equalities and Rough Equivalences.- Part II Rough Set Data Mining Activities.- Rough Clustering with Partial Supervision.- A Generic Scheme for Generating Prediction Rules Using Rough Sets.- Rough Web Caching.- Software Defect Classification: A Comparative Study of Rough-Neuro-Fuzzy Hybrid Approaches with Linear and Non-Linear SVMs.- Part III Rough Hybrid Models to Classification and Attribute Reduction.- Rough Sets and Evolutionary Computation to Solve the Feature Selection Problem.- Nature Inspired Population-based Heuristics for Rough Set Reduction.- Developing a Knowledge-based System using Rough Set Theory and Genetic Algorithms for Substation Fault Diagnosis.
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