Search for dissertations about: "support-vector machines"
Showing result 1 - 5 of 54 swedish dissertations containing the words support-vector machines.
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1. Fixed points, fractals, iterated function systems and generalized support vector machines
Abstract : In this thesis, fixed point theory is used to construct a fractal type sets and to solve data classification problem. Fixed point method, which is a beautiful mixture of analysis, topology, and geometry has been revealed as a very powerful and important tool in the study of nonlinear phenomena. READ MORE
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2. High-Performance Computing For Support Vector Machines
Abstract : Machine learning algorithms are very successful in solving classification and regression problems, however the immense amount of data created by digitalization slows down the training and predicting processes, if solvable at all. High-Performance Computing(HPC) and particularly parallel computing are promising tools for improving the performance of machine learning algorithms in terms of time. READ MORE
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3. Distributed and federated learning of support vector machines and applications
Abstract : Machine Learning (ML) has achieved remarkable success in solving classification, regression, and related problems over the past decade. In particular the exponential growth of digital data, makes using ML inevitable and necessary to exploit the wealth of information hidden inside the data. READ MORE
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4. Computational and spatial analyses of rooftops for urban solar energy planning
Abstract : In cities where land availability is limited, rooftop photovoltaic panels (RPVs) offer high potential for satisfying concentrated urban energy demand by using only rooftop areas. However, accurate estimation of RPVs potential in relation to their spatial distribution is indispensable for successful energy planning. READ MORE
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5. On Tracing Flicker Sources and Classification of Voltage Disturbances
Abstract : Developments in measurement technology, communication and data storage have resulted in measurement systems that produce large amount of data. Together with the long existing need for characterizing the performance of the power system this has resulted in demand for automatic and efficient information-extraction methods. READ MORE