Slavco Velickov

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The rapid advance in information processing systems in recent decades had directed engineering research towards the development of intelligent systems that can evolve models of natural phenomena automatically, ‘by themselves’, so to speak. In this respect, a wide range of machine learning techniques like decision trees, artificial neural networks (ANNs),(More)
The recently developed methods in nonlinear dynamics and chaos time series analysis are used in this study to analyze, delineate and quantify the underlying coastal water level and surge dynamics in the North Sea along several locations at the Dutch coast. This study analyzes seven water level and surge data sets, five of which characterize coastal(More)
Support Vector Machines (SVM) are emerging techniques which have proven successful in many traditionally neural network (NN) dominated applications. An interesting property of this approach is that it is an approximate implementation of the Structural Risk Minimization (SRM) induction principle that aims at minimizing a bound on the generalization error of(More)
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