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Artificial Neural Nets and Genetic Algorithms, 2001 Proceedings of the International Conference in Prague, Czech Republic, 2001

Langue : Anglais

Coordonnateurs : Kurkova Vera, Steele Nigel C., Neruda Roman, Karny Miroslav

Couverture de l’ouvrage Artificial Neural Nets and Genetic Algorithms
The first ICANNGA conference, devoted to biologically inspired computational paradigms, Neural Net­ works and Genetic Algorithms, was held in Innsbruck, Austria, in 1993. The meeting attracted researchers from all over Europe and further afield, who decided that this particular blend of topics should form a theme for a series of biennial conferences. The second meeting, held in Ales, France, in 1995, carried on the tradition set in Innsbruck of a relaxed and stimulating environment for the. exchange of ideas. The series has continued in Norwich, UK, in 1997, and Portoroz, Slovenia, in 1999. The Institute of Computer Science, Czech Academy of Sciences, is pleased to host the fifth conference in Prague. We have chosen the Liechtenstein palace under the Prague Castle as the conference site to enhance the traditionally good atmosphere of the meeting. There is an inspirational genius loci of the historical center of the city, where four hundred years ago a fruitful combination of theoretical and empirical method, through the collaboration of Johannes Kepler and Tycho de Brahe, led to the discovery of the laws of planetary orbits.
Part I: Plenary Talks and Tutorials: What Can a Neural Network Do without Scaling Activation Function? (Y. Ito); Ratio Scales Are Critical for Modeling Neural Synthesis in the Brain (T. L. Saaty); Hypermatrix of the Brain (T. L. Saaty); The Computational Capabilities of Neural Networks (J. Šíma).- Part II: Neural Networks – Theory: Activation Functions (N. C. Steele, C. R. Reeves, E.I. Gaura); A Simulation of Spiking Neurons by Sigmoid Neurons (V. Kvasnicka); Tightness of Upper Bounds on Rates of Neural-Network Approximation (V. Kurkova, M. Sanguineti); Incremental Function Approximation Based on Gram-Schmidt Orthonormalisation Process (B. Beliczynski); Wavelet Based Smoothing in Time Series Prediction with Neural Networks (U. Lotric, A. Dobnikar); Fitting Densities and Hazard Functions with Neural Networks (C. Reeves, C. Johnston); Optimization of Expensive Functions by Surrogates Created from Neural Network Ensembles (J. Pospíchal); Local-Global Neural Networks for Interpolation (C. E. Pedreira, L. C. Pedroza, M. Fariñas); Improving the Competency of Classifiers through Data Generation (H. L. Viktor, I. Skrypnik; Graded Rescaling in Hopfield Networks (X. Zeng, T. R. Martinez); Principles of Associative Computation (A. Wichert, B. Lonsinger-Miller); An Experimental Assessment of the Performance of Several Associative Memory Models (S. P. Turvey, S. P. Hunt, N. Davey, R. J. Frank); Recall Time in Densely Encoded Hopfield Network: Results from KFS Theory and Computer Simulation(A. A. Frolov, D. Husek, P. Combe, V. Snásel); On-Line Identification and Rule Extraction of Finite State Automata with Recurrent Neural Networks (I. Gabrijel, A. Dobnikar); Using Decision Surface Mapping in the Automatic Recognition of Images (C. Reeves, G. S. Billan); Competitive Learning and Its Convergence Analysis (Y.-J. Zhang, Z.-Q. Liu); Structural Information Control for Flexible Competitive Learning (R. Kamimura, T. Kamimura, T. R. Shultz); Recursive Learning Scheme for Recurrent Neural Networks Using Simultaneous Perturbation and Its Application (Y. Maeda); Reinforcement Learning for Rule Generation (D. Vogiatzis, A. Stafylopatis); Learning Feed-Forward Multi-Nets (R. S. Venema, L. Spaanenburg); Unlearning in Feed-Forward Multi-Nets (L. Spaanenburg); Context Neural Network for Temporal Correlation and Prediction (L. F. Mingo, L. Aslanyan, J. Castellanos, V. Riazanov, M. A. Díaz); A Pruning Self-Organizing Algorithm to Select Centers of Radial Basis Function Neural Networks (L. N. de Castro, F. J. Von Zuben); Modular Clustering by Radial Basis Function Network for Complexity Reduction in System Modeling (Ö. Ciftcioglu, S. Sariyildiz); A Fuzzy Approach to Sociodynamical Interactions (D. W. Pearson, G. Dray); An Immunological Approach to Initialize Feedforward Neural Network Weights (L. N. de Castro, F. J. Von Zuben); How Certain Characteristics of Cortical Frequency Representation May Influence Our Perception of Sounds (L. Beñušková); Long Short-Term Memory Learns Context Free and Context Sensitive Languages (F. A. Gers, J. Schmidhuber); An Artificial Neural Network Model Based on Neuroscience: Looking Closely at the Brain (J. L. G. Rosa); STARBRAIN and EUROBRAIN, Starlab’s and Europe’s Artificial Brain Projects: An Overview (H. de Garis).- Part III: Neural Networks – Applications: Application of Feature Extraction in Text-to-Speech Processing (V. Šebesta, J. Tucková); Gaussian Synapse Networks for Handwritten Character Recognition (J. L. Crespo, R. J. Duro); A Generic Pretreatment for Spiking Neuron Application on Lipreading with STANN (Spatio-Temporal Artificial Neural Networks) (R. Séguier, D. Mercier); A Comparison of a Neural Network and an Observer Approach for Detecting Faults in a Benchmark System (D. N. Shields, S. Du, E. Gaura); A Neuro-Fuzzy Image Analysis System for Biomedical Imaging Applications (L. Patino, M. Razaz); Real Time Identification and Control of a DC Motor Using Recurrent Neural Networks (I. Baruch, J. M. Flores, R. Garrido, B. Nenkova); Recurrent Neural Networks in a Mobile Robot Navigation Task (B. Ster); Angular Memory and Supervisory Modules in a Neural Architecture for Navigating NOMAD (C. Silva, M. Crisóstomo, B. Ribeiro); A Recurrent Neural Network for Controlling a Fed-Batch Fermentation of B. t. (J. B. Cortés, I. Baruch, L. V. Castro, V. V. Cervantes); A Draft on Modelling the Behaviour of Bioreactor Landfill Using Neural Nets (L. Landryova, J. P. Robinson); Neural Network Combustion Optimisation in Naantali Power Plant (J. Mäkilä, J.-P. Jalkanen); Control Sensitivity SVM for Imbalanced Data: A Case Study on Automotive Material (K. K. Lee, C. J. Harris, S. R. Gunn, P. A. S. Reed); Analysis of Defectoscopy Data To Be Used by Neural Classifier (J. Grman, R. Ravas, L. Syrova); NeuroHough: A Neural Network for Computing the Hough Transform (M. Köppen, A. Soria-Frisch, R. Vicente-García); Fast Iris Detection Using Cooperative Modular Neural Nets (H. M. El-Bakry); Symbolic Representation of a Multi-Layer Perceptron (F. Mouria-Beji); Software Generation of Random Numbers by Using Neural Network (C.-K. Chan, C.-K. Chan, L. M. Cheng); FPGA Implementation of a Spike-Based Sound Localization System (M. Ponca, C. Schauer); A Simulator to Parallelise Large Biologically-Inspired Artificial Neural Networks (Y. Boniface); Time Perception and Reinforcement Learning: A Neural Network Model of Animal Experiments (J. L. Shapiro, J. Wearden).- Part IV: Genetic Algorithms – Theory: ADFs: An Evolutionary Approach to Predicate Invention (C. Giraud-Carrier, C. J. Kennedy); The Convergence Behavior of the PBIL Algorithm: A Preliminary Approach (C. González, J. A. Lozano, P. Larrañaga); Information Dimension of a Population’s Attractor in a Binary Genetic Algorithm (P. Kies); An Evolutionary Approach to the Zero/One Knapsack Problem: Testing Ideas from Biology (A. Simoes, E. Costa); An Evolutionary Approach to Identification of Nonlinear Dynamic Systems (M. Witczak, J. Korbicz); Measures for Non-Stationary Optimization Tasks (K. Trojanowski, A. Obuchowicz); The True Nature of Multi-Dimensional Gaussian Mutation (A. Obuchowicz); Multimodal Function Optimization Using Species Conservation (M.-E. Balázs, L. Jianping, G. T. Parks, P. J. Clarkson); Automatic Feature Selection by Genetic Algorithms (M. Eberhardt, F. W. H. Kossebau, A. König); Feature Subset Selection Problems: A Variable-Length Chromosome Perspective (C. M. Guerra-Salcedo); Mining Numeric Association Rules with Genetic Algorithms (J. Mata, J. L. Alvarez, J. C. Riquelme); Takeover Times of Noisy Non-Generational Selection Rules that Undo Extinction (G. Rudolph); Evolutionary Algorithms Aided by Sensitivity Information (T. Burczynski, P. Orantek).- Part V: Genetic Algorithms – Applications: Ants and Graph Coloring (J. Shawe-Taylor, J. Žerovnik); Evolutionary Optimization of a Wavelet Classifier for the Categorization of Beat-to-Beat Variability Signals (H. A. Kestler, M. Höher, G. Palm); Genetic Implementation of a Classifier Based on Data Separation by Means of Hyperspheres (M. Jirina, jr., J. Kubalík, M. Jirina); Evolving Order Statistics Filters for Image Enhancement (C. Munteanu, A. Rosa); GA-Based Non-linear Harmonic Estimation (M. Bettayeb, U. Qidwai); Scheduling Multiprocessor Tasks with Correlated Failures Using Population Learning Algorithm (P. Jedrzejowicz, E. Ratajczak); Fuzzy Availability Agent in a Virtual Environment (J. R. King. M. Razaz); The Flowering of Fuzzy CoCo: Evolving Fuzzy Iris Classifiers (C. A. Peña-Reyes, M. Sipper); Genetic Algorithm Based Parameters Identification for Power Transformer Thermal Overload Protection (V. Galdi, L. Ippolito, A. Piccolo, A. Vaccaro); Optimal Municipal Bus Routing Using a Genetic Algorithm (J. M. Suiter, D. H. Cooley); Rostering with a Hybrid Genetic Algorithm (M. Gröbner, P. Wilke); Design of Discrete Non-Linear Two-Degrees-of-Freedom PID Controllers Using Genetic Algorithms (P. B. de Moura Oliveira); Modification of the Particle Swarm Optimizer for Locating All the Global Minima (K. E. Parsopoulos, M. N. Vrahatis).- Part VI: Soft Computing – Applications: Computational Issues in Model Predictive Control (L. Chisci, G. Zappa); Motor Control Using Adaptive Time-Delay Learning (C. Ungerer); Comoputer Aided Prototyping of Repititive Distributed Control (J. Stanczyk); On Structure of Local Models for Hybrid Controllers (T. V. Guy, M. Kárný); Cerebellar Climbing Fibers Anticipate Error in Motor Performance (Y. Burnod, M. Dufossé, A. A. Frolov, A. Kaladjian, S. Rízek); Model of Neurocontrol of Anthropomorphic Systems (A. Frolov, S. Rízek, M. Dufossé); A Neural Model for Animats Brain (G. Beslon, H. Soula, J. Favrel); A Fuzzy Logic System Applied in Lightning Models (A. N. de Souza, I. N. da Silva, J. A. C. Ulson).- Part VII: Hybrid Methods and Tools: Multi-Agent Environment for Hybrid AI Models (R. Neruda, P. Krušina, Z. Petrová); Using Neural Networks and Genetic Algorithms as Building Blocks for Artificial Life Simulations (G. Beuster); A Hybrid Intelligent System for Image Matching, Used as Preprocessing for Signature Verification (J. Valyon, G. Horváth); A GA-ANN for the Eulerian Cycle Problem (T. Tambouratzis); Design of RBF Networks by Cooperative/Competitive Evolution of Units (A. J. Rivera, J. Ortega, A. Prieto); Avoiding Local Minima in ANN by Genetic Evolution (R. Mendes, P. Vale, J. M. Sousa, J. A. Roubos); A Genetic Designed Beta Basis Function Neural Network for Approximating Multi-Variables Functions (C. Aouiti, A. M. Alimi, A. Maalej); Optimization with Implicitly Known Objective Functions Using RBF Networks and Genetic (H. Nakayama, M. Arakawa, R. Sasaki); Hybrid Model of Cooling Tower Based on First Principles and Neural Networks (N. Milosavljevic, H. Saxén); Dynamic Handwriting Recognition Based on an Evolutionary Neural Classifier (S. Gentric, L. Prevost, M. Milgram).- Part VIII: Probabilistic Models and Clustering: Initial Description of Multi-Modal Dynamic Models (M. Kárný, P. Nedoma, I. Nagy, M. Valecková); Factorized EM Algorithm for Mixture Estimation (I. Nagy, P. Nedoma, M. Kárný); Number of Components and Initialization in Gaussian Mixture Model for Pattern Recognition (P. Paclík, J. Novovicová); Parallel Factorised Algorithms for Mixture Estimation (M. Tichý, B. Kovár); Method for Artefact Detection and Suppression Using Alpha-Stable Distributions (L. Tesar, A. Quinn); Model Selection with Small Samples (M. Sugiyama, H. Ogawa); A Data-Reusing Stochastic Approximation Algorithm for Neural Adaptive Filters (D. P. Mandic, I. R. Krcmar, W. Sherliker, G. Smith); Robust On-Line Statistical Learning (E. Capobianco); Efficient Sequential Minimal Optimisation of Support Vector Classifiers (G. C. Cawley); Model Selection for Support Vector Machines via Adaptive Step-Size Tabu Search (G. C. Cawley); Data Clustering Based on a New Objective Function (Z.-Q. Liu, Y.-J. Zhang); Dynamical Cluster Analysis for the Detection of Microglia Activation (A. Baune, A. Wichert, G. Glatting F. T. Sommer); Interpretation of Event-Related fMRI Using Cluster Analysis (A. Wichert, A. Baune, J. Grothe, G. Grön, H. Walter, F. T. Sommer); A Special-Purpose Neural Network Recogniser To Detect Non-Random Pattern on Control Charts (A. Anglani, M. Pacella, Q. Semeraro); Data Mining and Automation of Experts Decision Process Applied to Machine Design for Furniture Production (G. Klene, A. Grauel, H. J. Convey, A. J. Hartley).- Part IX: Data Mining in Meteorology and Air Pollution: Estimating Hourly Solar Radiation on Tilted Surface via ANNs (M. Gazela, T. Tambouratzis); On the Typology of Daily Courses of Tropospheric Ozone Concentrations (E. Pelikán, K. Eben, J. Vondrácek, M. Dostál, P. Krejcír, J. Keder); GUHA Analysis of Air Pollution Data (D. Coufal); Application of the Surrogate Test to Detect Dynamic Non-Linearity in Ground-Level Ozone Time-Series from Berlin (U. Schlink, P. Haase); Nonlinearity and Prediction of Air Pollution (M. Paluš E. Pelikán, K. Eben, P. Krejcír, P. Juruš); On Nonlinear Processing of Air Pollution Data (R. Foxall, I. Krcmar, G. Cawley, S. Dorling, D. P. Mandic); On Predictability of Atmospheric Pollution Time Series (I. R. Krcmar, P. Mandic, R. J. Foxall); Estimating the Costs Associated with Worthwhile Predictions of Poor Air Quality (G. C. Cawley, S. R. Dorling, R. J. Foxall, D. P. Mandic); Modelling Air Pollution Time-Series by Using Wavelet Functions and Genetic Algorithms (G. Nunnari, L. Bertucco); Predicting Daily Average S02 Concentrations in the Industrial Area of Syracuse (Italy) (G. Nunnari, L. Bertucco, D. Milio); Forecasting of Air Pollution at Unmonitored Sites (S. Lopes, M. Niranjan, J. Oakley); Applications of Neural Networks in Processing and Regionalization of Radiation Data (L. Metelka, S. Kliegrová)

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