The material presented in the book is divided into two main parts: Keynotes, and Case Studies. Five keynotes written by W. Pedrycz, D. Dubois and H. Prade, M.M. Gupta, P.M. Frank, and T. Kaczorek deal with: introduction into the concept and basic technologies of computational intelligence (CI), role of fuzzy logic in information engineering, paradigms of fuzzy neural computing, intelligent methods in fault diagnosis of technical plants, and with models of two-dimensional (2D) systems which are useful in analysis of methods manifesting the learning ability, respectively. The second part provides the reader with a sampling of various applications of the methods (neural networks, genetic algorithms, fuzzy, and evolutionary systems) being the building blocks of the CI. However, a few contributions exceed this rather stiff frame of CI-definition.
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P.S. Szczepaniak: Preface.- Keynotes: W. Pedrycz: Computational Intelligence: An Introduction.- D. Dubois, H. Prade: Fuzzy Information Engineering and Soft Computing.- M.M. Gupta: Fuzzy Neural Computing.- P.M. Frank: AI Methods AI Fault Diagnosis.- T. Kaczorek: Positive 2D Linear Systems.- Case Studies: M. Al-Rawi, A. Materka: Voiced/Unvoiced Speech Signal Segmentation Using Wavelet Analysis.- D. Baczynski, P. Helt, M. Parol, P. Piotrowski: ANN and EA in Electrical Distribution Network Optimisation.- J. Balicki: Evolutionary Neural Networks for Solving Multiobjective Optimization Problems.- D. Barrios, I.M. Galván, P. Isasi, J. Ríos, J.M. Zaldívar: A New Neural Network Approach to Allow Predicative Control in Real Time.- G. Brzykcy: Modelling User Interaction in Prolog Programs.- L. Constant, P. Lagarrigues, B. Dagues, I. Rivals, L. Personnaz: Modeling of Electromechanical System Using Feedback Neural Network.- M. Dolínska, K.J. Cios: Dynamic Multiobjective Pricing Strategy Using Fuzzy Logic.- D.V. Filatova: Application of Dynamic Factor Model for the Training Process Prediction.- P. Golabek, W. Kosinski, M. Weigl: Adaptation of Learning Rate via Adaptation of Weight Vector in Modified M-Delta Networks.- Z. Gontar: Electronic Distribution Planning - Lessons in Simulated Annealing.- Z.S. Hippe: Computational Intelligence - An Example of Searching Regularities.- A. Józwik, K. Strzecha: Neuronlike Net, Standard k-NN Classifier and Net of k-NN Classifiers. An Experimental Comparison Study.- J. Kabzinski, P. Wozniak: Adaptive Plus Fuzzy/Neural Controllers for MIMO Nonlinear Plants.- J. Kazimierczak: On Solving Some Artificial Intelligence Problems by Using Evolvable Hardware.- E. Kacki,B.A. Ostrowska, J. Stempczynska: Diagnostic Algorithm Based on Expert Matrix Obtained by Monte-Carlo Method.- S.S. Lam, X. Cai: Distance Measures of Fuzzy Numbers.- S.J. Langdell, J.C. Mason: Exploiting the Relevance of Input Variables to Improve Classification of Biomedical Data.- H.S. Lopes: A Medical Diagnostic System Optimization Using Parallel Genetic Algorithms.- Z. Lubosny: Identification of Dynamic Object by Neural Network.- A. Materka, M. Strzelecki: Observation Domain Partitioning by Means of ANNs in Real-Time Parameter Estimation Systems.- W. Miszalski, Z. Swiatnicki, R. Wantoch-Rekowski: The Air Force Development Using Experts' Knowledge and Common Sense.- S.K. Mitra, C.A. Murthy, M.K. Kundu: Digital Image Magnification Using Fractal Operators and Genetic Algorithm.- J.M. Molina-López, P. Isasi-Vinuela, A. Sanchis de Miguel: Expert System-Neural Network: A Hybrid System for Predictive Control.- K.W. Przytula, D. Thompson: Analysis of Trained Neural Networks.- J. Ratynska: An Inference Model and Natural Language Processing.- A. Riid, E. Rüstern: Fuzzy Modeling and Controlling of Fed-Batch Fermentation.- D. Rutkowska, R. Norwicki, L. Rutkowski: Singleton and Non-Singleton Fuzzy Systems with Nonparametric Defuzzification.- P. Strumillo, W. kaminski, J. Skrzypski: Modelling and Interpolation of Seasonal Air Temperature Changes in Central Europe.- Z. Swiatnicki, R. Semklo: The Multilayer Perceptron for Object Recognition Based on Radar Signals.- Z. Swiatnicki, R. Wantoch-Rekowski: The Stars Recognition with Neural Network Based on Special Representation of Celestial Constellation.- M. Swiercz: Modular Neural Networks for Modeling of a Nonlinear Dynamic System. A Case Study.- G.E. Tsekouras, G.V. Bafas, S.K. Stoyanov: Multivariable
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