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Showing result 11 - 15 of 60 essays matching the above criteria.
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11. Investigation of Machine Learning Regression Techniques to Predict Critical Heat Flux
University essay from Uppsala universitet/Avdelningen för systemteknikAbstract : A unifying model for Critical Heat Flux (CHF) prediction has been elusive for over 60 years. With the release of the data utilized in the making of the 2006 Groeneveld Lookup table (LUT), by far the largest public CHF database available to date, data-driven predictions on a large variable space can be performed. READ MORE
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12. Estimation of dissolved organic carbon from inland waters using remote sensing data and machine learning
University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapAbstract : This thesis presents the first attempt to estimate Dissolved Organic Carbon (DOC) in inland waters over a large-scale area using satellite data and machine learning (ML) methods. Four ML approaches, namely Random Forest Regression (RFR), Support Vector Regression (SVR), Gaussian Process Regression (GPR), and a Multilayer Backpropagation Neural Network (MBPNN) were tested to retrieve DOC using a filtered version of the recently published open source AquaSat dataset with more than 16 thousand samples across the continental US matched with satellite data from Landsat 5, 7 and 8 missions. READ MORE
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13. Utilizing Genetic Algorithm and Machine Learning to Optimize a Control System in Generators : Using a PID controller to damp terminal voltage oscillations
University essay from Mälardalens universitet/Akademin för ekonomi, samhälle och teknikAbstract : Hydropower is an important part of renewable power production in Sweden. The voltage stability of the already existing hydropower needs to be improved. One way to do this is by improving the control system that damp terminal voltage oscillations. READ MORE
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14. Optimal Q-Space Sampling Scheme : Using Gaussian Process Regression and Mutual Information
University essay from Uppsala universitet/Avdelningen för systemteknikAbstract : Diffusion spectrum imaging is a type of diffusion magnetic resonance imaging, capable of capturing very complex tissue structures, but requiring a very large amount of samples in q-space and therefore time. The purpose of this project was to create and evaluate a new sampling scheme in q-space for diffusion MRI, trying to recreate the ensemble averaged propagator (EAP) with fewer samples without significant loss of quality. READ MORE
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15. Predicting Quality of Experience from Performance Indicators : Modelling aggregated user survey responses based on telecommunications networks performance indicators
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : As user experience can be a competitive edge, it lies in the interest of businesses to be aware of how users perceive the services they provide. For telecommunications operators, how network performance influences user experience is critical. To attain this knowledge, one can survey users. READ MORE