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ویرایش:
نویسندگان: Yuehui Chen. Ajith Abraham
سری: Intelligent Systems Reference Library, Volume 2
ISBN (شابک) : 9783642017995, 3642017991
ناشر: Springer
سال نشر: 2009
تعداد صفحات: 211
زبان: English
فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود)
حجم فایل: 3 مگابایت
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در صورت تبدیل فایل کتاب Tree-Structure Based Hybrid Computational Intelligence. Theoretical Foundations andApplications به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
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3642047386 front-matter front-matter_001 Part I Foundations of Computational Intelligence front-matter_002 Part II Flexible Neural Trees fulltext Foundations of Computational Intelligence Introduction Evolutionary Algorithms Genetic Programming Estimation of Distribution Algorithm Population-Based Incremental Learning Probabilistic Incremental Program Evolution Swarm Intelligence Particle Swarm Optimization Ant Colony Optimization Artificial Neural Networks Architecture and Learning Algorithm Multilayer Perceptron Back-Propagation Algorithm Evolutionary Algorithm Based Training Self Organizing Feature Maps Radial Basis Function Recurrent Neural Networks Adaptive Resonance Theory Fuzzy Systems The Definition of Fuzzy Sets Takagi-Sugeno Fuzzy Model Universal Approximation Property Fuzzy Expert Systems - Design Challenges Probabilistic Computing Hybrid Intelligent Systems Models of Hybrid Intelligent Systems front-matter_003 Part III Hierarchical Neural Networks fulltext_001 Flexible Neural Tree: Foundations and Applications Introduction to Flexible Neural Tree Flexible Neural Tree Algorithms Encoding and Evaluation Flexible Neuron Instructor Fitness Function Structure and Parameter Learning Flexible Neural Tree Applications Exchange Rate Forecasting Face Recognition Microarray-Based Cancer Classification Protein Fold Recognition Multi Input Multi Output Flexible Neural Tree Representation and Calculation of the MIMO FNT Hybrid Algorithm for Structure and Parameter Learning Hybrid Algorithm for Flexible Neural Tree Model Illustrative Examples Ensemble of Flexible Neural Tree The Basic Ensemble Method The Generalized Ensemble Method The LWPR Method Stock Index Forecasting Problem Stock Index Forecasting Experimental Illustrations front-matter_004 Part IV Hierarchical Fuzzy Systems fulltext_002 Hierarchical Neural Networks Hierarchical Radial Basis Function Neural Networks The Radial Basis Function Network Automatic Design of Hierarchical Radial Basis Function Network Tree Structure Optimization by Extended Compact Genetic Programming (ECGP) Parameter Optimization Using Differential Evolution Algorithm Procedure of The General Learning Algorithm Variable Selection in the HRBF Network Paradigms Experimental Illustrations Face Recognition Hierarchical B-Spline Neural Networks The B-Spline Network Automatic Design of HB-Spline Network Encode and Calculation for HB-Spline Tree Structure and Parameter Optimization Procedure of the General Learning Algorithm Variable Selection in the Hierarchical B-Spline Network Paradigms Experimental Illustrations Wisconsin Breast Cancer Detection Time-Series Forecasting Hierarchical Wavelet Neural Networks Wavelet Neural Network Automatic Design of Hierarchical Wavelet Neural Network Ant Programming for Evolving the Architecture of HWNN Parameter Optimization Using Differential Evolution Algorithm Procedure of the General Learning Algorithm for HWNN Variable Selection Using HWNN Paradigms Experimental Illustrations Application to Jenkins-Box Time-Series front-matter_005 Part V Reverse Engineering of Dynamical Systems fulltext_003 Hierarchical Fuzzy Systems Introduction Takagi-Sugeno Fuzzy Inference System (TS-FS) Hierarchical TS-FS: Encoding and Evaluation Encoding Evaluation Objective Function Evolutionary Design of Hierarchical TS-FS Algorithm for Designing Hierarchical TS-FS Model Feature/Input Selection with Hierarchical TS-FS Experimental Illustrations Systems Identification Chaotic Time-Series of Mackey-Glass Iris Data Classification Wine Data Classification front-matter_006 Part VI Conclusions and Future Research fulltext_004 Reverse Engineering of Dynamic Systems Introduction Calculation and Representation of Additive Models Hybrid Algorithm Tree-Structure Based Evolutionary Algorithm Evolving an Optimal or Near-Optimal Structure of Additive Model Parameter Optimization Summary of General Learning Algorithm Experimental Illustrations Discussions Inferring a System of Differential Equations Inference of Differential Equation Models by Multi Expression Programming Structure Optimization by the MEP Parameter Optimization by Particle Swarm Optimization Algorithm Fitness Definition Summary of Algorithm Modeling Chemical Reactions Simple Chemical Reaction Model Two-Species Lotka-Volterra Model Bimolecular Reaction Inferring Gene Regulatory Networks The Small Artificial Gene Regulatory Network The Large-Scale Artificial Gene Regulatory Network with Noisy Environment fulltext_005 Concluding Remarks and Further Research Limitations of Conventional Computational Intelligence Towards Tree-Structure Based Hierarchical Hybrid Computational Intelligence Tree Structure Based Evolutionary Computation Models Hierarchical Hybrid Computational Intelligence Framework Static and Dynamical Models back-matter