Titlebook: Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing; An Evolutionary Appr Patricia Melin,Oscar Castillo Book 2005 Sprin

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Book 2005genetic algorithms. Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of pattern recognition syst

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monopoly

Intuitionistic and Type-2 Fuzzy Logic,can also be considered an extension of type-1 fuzzy sets in the sense that intuitionistic fuzzy sets not only use the membership function, but also a non-membership function to represent the uncertainty of belonging to a fuzzy set.

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Supervised Learning Neural Networks,gorithms. Third, we give a brief review of the radial basis neural networks. Finally, we end the chapter with a description of the adaptive neuro-fuzzy inference system (ANFIS) methodology. We consider this material necessary to understand the new methods for pattern recognition that will be presented in the final chapters of this book.

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學術討論會

1434-9922 of hybrid intelligent systems to real-world problems of fac.This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms. Hybrid intelligent systems that combine several soft computing techniq

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Epidural-Space

Clustering with Intelligent Techniques, real-world applications there is very often no clear boundary between clusters so that fuzzy clustering is often a good alternative to use. Membership degrees between zero and one are used in fuzzy clustering instead of crisp assignments of the data to clusters.