§16§The global purpose of IWANN conferences has been to provide a broad and - terdisciplinary forum for the interplay between neuroscience and computation. Our dream has been, and still is: (1) ?nd ways to understand the physiol- ical, symbolic and cognitive nature of the nervous system (NS) with the help of computational and engineering tools; and (2) ?nd rich and insightful sources of inspiration in biology, to develop new materials, mechanisms and probl- solving methods (PSM) of value in engineering and computation. As all of us knowwell, this dreamstarted with the AncientGreeks, reappearedin the fo- dational stage of neurocybernetics and bionics, and is now broadly accepted in the scienti?c community under di?erent labels such as computational neu- science(CN) andarti?cialneuralnets (ANN), orgenetic algorithmsandhybrid neuro-fuzzy systems. We have also to recognize that there is a considerable lack of credibility associated with CN and ANN among some researchers, both from biology §16§ and from the engineering and computation area. Potential causes of this scepticism could be the lack of methodology, formal tools, and real-world applications, in the engineering area, and the lack also of formal tools for cognitive process modeling. There is also the possibility of the computational paradigm being inappropriate to explain cognition, because of the representational character ofanycomputationalmodel. Some moresituated approachesarelookingback to the neurophysiological epistemology of the 1960 s (mind in a body) to searchdirectlyforthemechanismsthatcouldembodythecognitiveprocess,and this means some fresh air for our old dream of connectionism. §04§Nets Design.- Applications in Robotics.- Sources Separation.- Genetics Algorithms.- Soft-Computing.- Images.- Medical Applications.- Other Applications. §04§s.- A Genetic Algorithm for Controlling Elevator Group Systems.- Protein Structure Prediction Using Evolutionary Algorithms Hybridized with Backtracking.- Hybridizing a Genetic Algorithm with Local Search and Heuristic Seeding.- A Genetic Algorithm for Assembly Sequence Planning.- Genetic Algorithm applied to Paroxysmal Atrial Fibrillation Prediction.- Optimizing supply strategies in the Spanish Electrical Market.- Improving the Efficiency of Multiple Sequence Alignment by Genetic Algorithms.- A real application example of a control structure selection by means of a multiobjective genetic algorithm.- Weighting and Feature Selection on Gene-Expression data by the use of Genetic Algorithms.- Supervised Segmentation of the Cervical Cell Images by using the Genetic Algorithms.- Using Genetic Algorithms for solving partitioning problem in codesign.- Soft-Computing.- Neuro-Fuzzy Modeling Applied to GIS: a Case Study for Solar Radiation.- Evolutionary Multi-Model Estimators for ARMA Syst §04§em Modeling and Time Series Prediction.- Real-Coded GA for Parameter Optimization in Short-Term Load Forecasting.- Parallel Computation of an Adaptive Optimal RBF Network Predictor.- New Method for Filtered ICA Signals Applied To Volatile Time Series..- Robust Estimation of Confidence Interval in Neural Networks applied to Time Series.- Modelling the HIV-AIDS Cuban Epidemics with Hopfield Neural Networks.- Comparison of Neural Models, Off-line and On-line Learning Algorithms for a Benchmark Problem.- Using Neural Networks in a Parallel Adaptative Algorithm for the System Identification Optimization.- Nonlinear Parametric Model Identification using Genetic Algorithms.- Input-Output Fuzzy Identification of Nonlinear Multivariable Systems. Application to a Case of AIDS Spread Forecast.- Recovering Missing Data with Functional and Bayesian Networks.- Estimation of train speed via neuro-fuzzy techniques.- Neuro-Fuzzy Techniques for Image Tracking.- Images.- A Comparative Study of Fuzzy
