05087nam 2200673Ia 450 991078499890332120230828213040.01-281-37912-39786611379124981-277-392-4(CKB)1000000000407569(EBL)1679470(OCoLC)815571423(SSID)ssj0000098335(PQKBManifestationID)11988629(PQKBTitleCode)TC0000098335(PQKBWorkID)10132186(PQKB)11380382(MiAaPQ)EBC1679470(WSP)00006072(Au-PeEL)EBL1679470(CaPaEBR)ebr10201443(CaONFJC)MIL137912(EXLCZ)99100000000040756920061019d2006 uy 0engur|n|---|||||txtccrAdvances in computational intelligence[electronic resource] theory & applications /Fei-Yue Wang, Derong LiuToh Tuck Link, Singapore ;New Jersey World Scientificc20061 online resource (478 p.)Series in intelligent control and intelligent automation ;v. 5Description based upon print version of record.981-256-734-8 Includes bibliographical references and index.Contents ; Preface ; List of Contributors ; 1 A Quest for Granular Computing and Logic Processing ; 1.1 Introduction ; 1.2 Granular Computing ; 1.3 Granular Computing and Logic: Synergistic Links ; 1.4 Main Categories of Fuzzy Logic Processing Units1.5 A General Topology of the Network 1.6 Interpretation Issues of Logic Networks ; 1.7 Conclusions ; Bibliography ; 2 Abstraction and Linguistic Analysis of Conventional Numerical Dynamic Systems ; 2.1 Introduction ; 2.2 Type-I Linguistic Dynamic Systems2.3 Type-II Linguistic Dynamic Systems 2.4 Linguistic Control Design for Goal States Specified in Words ; 2.5 Conclusions ; Bibliography ; 3 Slicing: A Distributed Learning Approach ; 3.1 Introduction ; 3.2 Slicing ; 3.3 Variance Reduction in Slicing ; 3.4 Experiments3.5 Analysis 3.6 Discussion ; 3.7 Conclusions ; Bibliography ; 4 Marginal Learning Algorithms in Statistical Machine Learning ; 4.1 Introduction ; 4.2 Classification Problems and Margin ; 4.3 Maximal Margin Algorithm in SVM4.4 Unbalanced Classification Problems and Weighted Maximal Margin Algorithms 4.5 The n-Unsupervised Learning Problems and Margin ; 4.6 Some Marginal Algorithms for One-Class Problems ; 4.7 Some New Algorithms of Clustering Problems ; 4.8 New Marginal Algorithms for PCA4.9 Conclusions Computational Intelligence (CI) is a recently emerging area in fundamental and applied research, exploiting a number of advanced information processing technologies that mainly embody neural networks, fuzzy logic and evolutionary computation. With a major concern to exploiting the tolerance for imperfection, uncertainty, and partial truth to achieve tractability, robustness and low solution cost, it becomes evident that composing methods of CI should be working concurrently rather than separately. It is this conviction that research on the synergism of CI paradigms has experienced significantSeries in intelligent control and intelligent automation ;v. 5.Artificial intelligenceComputational intelligenceArtificial intelligence.Computational intelligence.006.3Wang Fei-Yue1534217Liu Derong66913MiAaPQMiAaPQMiAaPQBOOK9910784998903321Advances in computational intelligence3781580UNINA