Soft Computing in Industrial Applications -

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Résumé :
1: Fuzzy Computing.- Fuzzy Process Model Development with Missing Data.- Decomposed Fuzzy Models for Modelling and Identification of Dynamic Systems.- Investigation of Least Square Fuzzy Identification via a Virtual Higher Resolution Fuzzy Model.- Fuzzy Morphologies Revisited.- A Design Method of Stable Non-separate Controller Using Symbolic Expressions.- Adjustment of Identified Fuzzy Measures.- Design and Application of Block-Oriented Fuzzy Models - Fuzzy Hammerstein Model.- Evolving Fuzzy Detectives: An Investigation into the Evolution of Fuzzy Rules.- Fuzzy Logic Two-phase Traffic Signal Control for Coordinated One-way Streets.- Clustering Models Extracting Dynamic and Non-Dynamic Changes for 3-Way Data.- 2: Neuro Computing.- Identification of Nonlinear Multivariable Process by Neural Networks: Open-loop and Closed-Loop Case Studies.- Modelling Batch Learning of Restricted Sets of Examples.- Neural Networks with Hierarchically Structured Information and its Unlearning Effects.- Discussion of Reliability Criterion for US Dollar Classification by LVQ.- Facility Location Using Neural Networks.- Building Maps of Workspace for Autonomous Mobile Robots Using Self-Organizing Neural Network.- Neural Network Parameter Estimation and Dimensionality Reduction in Power System Voltage Stability Assessment.- Neural Networks-based Friction Compensation with Application in Servo Motor Systems.- Linear and Neural Dynamical Models for Energy Flows Prediction in Facility Systems.- An Optimal VQ Codebook Design Using the Co-adaptation of Learning and Evolution.- 3: Evolutionary Computation.- An Emergence of Coordinated Communication in Populations of Agents with Evolution Simulated by Genetic Algorithm.- Migration and Population Dynamics in Distributed Coevolutionary Algorithm.-Royal Road Encodings and Schema Propagation in Selective Crossover.- An Evolutionary Approach for the Design of Natural Language Parser.- GA-Based Identification of Unknown Structured Mechatronics System.- Integrating Genetic Algorithms and Interactive Simulations for Airbase Logistics Planning.- Evaluation of Virtual Cities Generated by Using a Genetic Algorithm.- 4: Probabilistic Computing.- Minimizing Real Functions by Scout.- Qualitative Similarity.- Survival Probability for Uniform Model on Binary Tree: Critical Behavior and Scaling.- Stochastic Modelling of Multifractal Exchange Rates.- Bayesian State Space Modeling for Nonlinear Nonstationary Time Series.- Noise Induced Congestion in Coupled Map Optimal Velocity Model of Traffic Flow.- Geometrical View on Mean-Field Approximation for Solving Optimization Problems.- Probabilistic Computational Method in Image Restoration Based on Statistical-Mechanical Technique.- Bayesian Neural Networks: Case Studies in Industrial Applications.- 5: Hybrid Methods, Chaos, and Immune Networks.- Multivariable Predictive Control Based on Neural Network Model and Simplex-Evolutionary Hybrid Optimization.- Permeability Prediction in Petroleum Reservoir using a Hybrid System.- A Performance Comparison of Chaotic Simulated Annealing Models for Solving the N-Queen Problem.- Study on the Idiotypic Network Model for the Feature Extraction of Patterns.- 6: Rough Sets.- Rough Set Based Uncertainty Management for Spatial Databases and Geographical Information Systems.- Soft Computing for Evolutionary Information Systems - Potentials of Rough Sets.- Towards Rough Set Based Concept Modeler.- 7: Image Processing.- Still Images Compression Using Fractal Approximation, Wavelet Transform and Vector Quantization.- N-dimensional Frameworks for theApplication of Soft Computing to Image Processing.- Computational Autopoiesis for Texture Analysis.- Novel Approach in Watermarking of Digital Image.- A Fuzzy Region-Growing Algorithm for Segmentation of Natura...

Sommaire:
This book contains recent theoretical innovations and a comprehensive collection of industrial applications in the emerging field of Soft Computing. Soft computing is a new form of artificial intelligence and it consists of four core methodologies: Fuzzy Computing, Neuro Computing, Evolutionary Computation, and Probabilistic Computing. These individual techniques are clearly complementary or synergistic rather than competitive. Therefore, it is a common practice to combine two or three methodologies when solving complex problems. Also the systematic fusion of soft computing and hard computing is a highly potential alternative to be considered. Soft computing methodologies are suitable for various real-world applications, because the available information and system knowledge are often imprecise, un? certain, or partially even incorrect. To handle such demanding conditions and obtain the required robustness with pure hard computing would typically be either very difficult or expensive. This book is a unique collection of technical articles providing a thorough overview of the state-of-the-art theory and industrial applications. The core articles on evolutionary computation, fuzzy computing, and neuro computing are of particular interest to researchers and practicing engineers....