Fuzzy mathematical approach to pattern recognition
Fuzzy mathematical approach to pattern recognition
Digital image processing (2nd ed.)
Digital image processing (2nd ed.)
Classifier systems and genetic algorithms
Artificial Intelligence
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Fuzzy logic, neural networks, and soft computing
Communications of the ACM
Soft computing in case based reasoning
Soft computing in case based reasoning
Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory
Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms for Pattern Recognition
Genetic Algorithms for Pattern Recognition
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing
Digital Picture Processing
Rough fuzzy MLP: knowledge encoding and classification
IEEE Transactions on Neural Networks
| Hi-index | 0.00 |
Relevance of fuzzy logic, artificial neural networks, genetic algorithms and rough sets to pattern recognition and image processing problems is described through examples. Different integrations of these soft computing tools are illustrated. Evolutionary rough fuzzy network which is based on modular principle is explained, as an example of integrating all the four tools for efficient classification and rule generation, with its various characterstics. Significance of soft computing approach in data mining and knowledge discovery is finally discussed along with the scope of future research.