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Titlebook: Artificial Intelligence Applications and Innovations; 8th IFIP WG 12.5 Int Lazaros Iliadis,Ilias Maglogiannis,Harris Papadopo Conference pr

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楼主: DIGN
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Combination of M-Estimators and Neural Network Model to Analyze Inside/Outside Bark Tree Diameters was to develop a Multi-Layer Perceptron neural network model which considered significant variables from an a priori developed robust regression model. The application of robust regression could be considered in selecting the input variables in a neural network model.
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Support Vector Machine Classification of Protein Sequences to Functional Families Based on Motif Selrt from presenting computational efficiency allowed for ranking the selected features. The experimental evaluation demonstrated the usefulness of the aforementioned approach, whereas the individual ranking for the three selection algorithms presented significant agreement.
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A Representational MDL Framework for Improving Learning Power of Neural Network Formalismsrepresentable with these networks (in contrast to classical ANNs) and that makes them easily learnable from training datasets according to a developed method of ANN architecture optimization. Methodology for comparing quality of different representations is illustrated by applying developed method in time series prediction and robot control.
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1868-4238 logic, classification - pattern recognition, multi-agent systems, multi-attribute DSS, clustering, image-video classification and processing, and engineering applications of AI and artificial neural networks.978-3-642-43653-6978-3-642-33409-2Series ISSN 1868-4238 Series E-ISSN 1868-422X
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Applications with asyncio and Twisted of such an information system through the use of the London Plan case study. An application of such a system is outlined by means of a probabilistic knowledge based IS which is developed by Influence Diagrams and can be utilized as an Environmental policy modeler and/or DSS.
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Using the CSLA .NET Base Classes,converges to the desired object boundary very fast. The theoretical properties and various experiments presented demonstrate that the proposed fuzzy energy-based active contour is better and more robust than classical snake methods based on the gradient or other kind of energies.
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