Titlebook: Applications of Computational Intelligence; 5th IEEE Colombian C Alvaro David Orjuela-Cañón,Jesus Lopez,Juan Carlos Conference proceedings

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,Design of a Segmentation and Classification System for Seed Detection Based on Pixel Intensity Threon system of agricultural products to satisfy product quality requirements. This chapter employs artificial vision techniques to classify seeds in RGB images. As a first step, an algorithm based on pixel intensity threshold is developed to detect and classify a set of different seed types, such as r

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,Classification of Focused Perturbations Using Time-Variant Functional Connectivity with rs-fmri,al level. Those effects can be studied using time-varying functional connectivity (TVFC) based on functional magnetic resonance imaging at rest (rs-fMRI). The characteristics of these alterations could be modeled using machine learning algorithms for patient classification. This study used hidden Ma

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: Analysis of Features for Protein Localization Classification Employing Fusion Data,ation has rapidly grown. In this case a comparison of two sources of this information was employed to determine protein localization in . cells. Models as support vector machines, artificial neural networks and random forest were compared for the prediction of protein localization. The sources of da

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,Optimizing a Dynamic Sliding Mode Controller with Bio-Inspired Methods: A Comparison,cience and engineering. This paper compares bio-inspired algorithms to better understand and measure how well they find the best tuning parameters for a Dynamic Sliding Mode Control for integrating systems with an inverse response and dead time. The comparison includes four bioinspired algorithms: p

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A Robust Controller Based on LAMDA and Smith Predictor Applied to a System with Dominant Time Delayith dominant dead time. Due to the non-linearity generated by the dead time, the application of an additional Smith Predictor structure is proposed to improve the system’s response when reference changes and disturbances occur around the operating point in which the system works. The controller is v

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,Comparison of the Performance of Two Neural Network Models with Parameter Optimization for the Predch for the best characteristics of the network is carried out with a heuristic model, which uses a genetic algorithm to vary the different parameters of the network, the solutions explored are 5000 in each independent experiment, out of a total of 15 independent experiments that reduces the probabil

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