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Titlebook: Hybrid Artificial Intelligent Systems; 6th International Co Emilio Corchado,Marek Kurzyński,Michał Woźniak Conference proceedings 2011 Spri

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Diagnosis of Partial Discharge Using Self Organizing Maps and Hierarchical Clustering – An Approachrlaying insulation defects or source that generate PD. The results present different patterns using a hibrid method with Self Organizing Maps (SOM) and Hierarchical clustering, this combination constitutes an excellent tool for exploration analysis of massive data like partial discharge on undergrou
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Bayesian Segmentation of Magnetic Resonance Images Using the ,-Stable Distributioner (WM) are modelled using a mixture of .-stable distributions. A Bayesian .-stable mixture model for histogram data is used and the unknown parameters are sampled using the Metropolis-Hastings algorithm, therefore, voxel intensity information is included in the model via a parameterized mixture of
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Investigation of Genetic Algorithms with Self-Adaptive Crossover, Mutation, and Selectionhms were then compared, with respect to convergence, with a traditional genetic one, which contained constant rates of mutation and crossover. The experiments were conducted on six benchmark functions including two unimodal functions, three multimodal with many local minima, and one multimodal with
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Hybrid Multi-agent System for Knowledge Management in Distributed Control Systemper deals with knowledge management based on Hybrid Multi-Agent System environment and the presented solutions are intended to enable dual abstraction of DCS both for ontology and control system design in a platform independent way. Hybrid Multi-Agent based software systems successfully join both re
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SVM with Bounds of Confidence and PLS for Quantifying the Effects of Acupuncture on Migraine Patientice, is effective for fighting migraine. To this purpose two different groups of patients are randomly collected and received . and . acupuncture, respectively. Acupuncture effects on brain perfusion patterns can be measured quantitatively by dealing with the images in a classification context. Part
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An Intelligent Automated Recognition System of Abnormal Structures in WCE Images in medical diagnosis by automatically detecting images containing pathological alterations in an 8-hour-long WCE video. We focus on three classes of pathologies – ulcers, bleedings and petechia – since they are typical for several diseases of the intestines. The main contribution is the performance
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