Search for dissertations about: "Support Vector Machine"

Showing result 1 - 5 of 69 swedish dissertations containing the words Support Vector Machine.

  2. 1. Protein Model Quality Assessment : A Machine Learning Approach

    Author : Karolis Uziela; Arne Elofsson; Liam McGuffin; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Protein Model Quality Assessment; structural bioinformatics; machine learning; deep learning; support vector machine; proq; Artificial Neural Network; protein structure prediction; Biochemistry towards Bioinformatics; biokemi med inriktning mot bioinformatik;

    Abstract : Many protein structure prediction programs exist and they can efficiently generate a number of protein models of a varying quality. One of the problems is that it is difficult to know which model is the best one for a given target sequence. Selecting the best model is one of the major tasks of Model Quality Assessment Programs (MQAPs). READ MORE

  4. 2. Failure diagnostics using support vector machine

    Author : Yuan Fuqing; Thomas Lindblad; Luleå tekniska universitet; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Drift och underhållsteknik; Operation and Maintenance;

    Abstract : Failure diagnostics is an important part of condition monitoring aiming to identify incipient failures in early stages. Accurate and efficient failure diagnostics can guarantee that the operator makes the correct maintenance decision, thereby reducing the maintenance costs and improving system availability. READ MORE

  5. 3. Voice for Decision Support in Healthcare Applied to Chronic Obstructive Pulmonary Disease Classification : A Machine Learning Approach

    Author : Alper Idrisoglu; Johan Sanmartin Berglund; Blekinge Tekniska Högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; Automated decision-support; Classification; Machine Learning; Voice-affecting disorders; Voice dataset; Voice Features; Chronic Obstructive pulmonary disease COPD ; Tillämpad hälsoteknik; Applied Health Technology;

    Abstract : Background: Advancements in machine learning (ML) techniques and voice technology offer the potential to harness voice as a new tool for developing decision-support tools in healthcare for the benefit of both healthcare providers and patients. Motivated by technological breakthroughs and the increasing integration of Artificial Intelligence (AI) and Machine Learning (ML) in healthcare, numerous studies aim to investigate the diagnostic potential of ML algorithms in the context of voice-affecting disorders. READ MORE

  6. 4. Fixed points, fractals, iterated function systems and generalized support vector machines

    Author : Xiaomin Qi; Sergei Silvestrov; Anatoliy Malyarenko; Daniel Andren; Viktor Abramov; Mälardalens högskola; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; support vector machine; fixed points; iterated function system; variational inequality; Mathematics Applied Mathematics; matematik tillämpad matematik;

    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

  7. 5. Machine learning for identification of brain activity patterns with applications in gentle touch processing

    Author : Malin Björnsdotter Åberg; Göteborgs universitet; []
    Keywords : Somatosensory; Machine learning; Pattern recognition; fMRI; Support vector machines; Neuroscience; Brain; BOLD; Signal processing; Artificial intelligence; Touch; Human; Unmyelinated; Sensory; Affective;

    Abstract : Since the first mention of artificial intelligence in the 1950s, the field of machine learning has provided increasingly appealing tools for recognition of otherwise unintelligible pattern representations in complex data structures. Human brain activity, acquired using functional magnetic resonance imaging (fMRI), is a prime example of such complex data where the utility of pattern recognition has been demonstrated in a wide range of studies recently (Haynes et al. READ MORE