Browsing NTNU Open by Author "Langseth, Helge"
Now showing items 21-40 of 113
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Autonomous Localization and Tracking for UAVs using Kalman Filtering
Jansen, Johan (Master thesis, 2014)Quadcopters and other drones have become more popular as they become more af- fordable and easier to use. As the accessibility increases, people discover new fields of application and one such potential use is for filming ... -
Bankrupcy Prediction for BDO Norway
Verma, Shivam (Master thesis, 2020)Konkursprediksjon er et fagfelt som vekker mye interesse på grunn av dets mange bruksområder. I dette prosjektet har det blitt tatt en praktisk tilnærming til konkursprediksjon, der funn fra litteraturen har blitt brukt ... -
Bayesian networks with applications in reliability analysis
Langseth, Helge (Dr. ingeniøravhandling, 0809-103X; 2002:121, Doctoral thesis, 2002)A common goal of the papers in this thesis is to propose, formalize and exemplify the use of Bayesian networks as a modelling tool in reliability analysis. The papers span work in which Bayesian networks are merely used ... -
Beating the bookmakers - Using artificial neural networks to profit from football betting
Borøy-Johnsen, Simon (Master thesis, 2017)Artificial Neural Networks (ANNs) have throughout the years been used for several different purposes. Problems spanning from image classification to text generation have all been subject to ANNs. In this report, ANNs were ... -
Classification of Marine Vessels using Sonar Data and a Neural Network
Gimse, Håkon (Master thesis, 2017)A submarine navigator have to keep track of surrounding ships in order to avoid collision and to gain a tactical advantage. This is currently done manually by a sonar operator, trained to listen through the water and ... -
Collaborative Filtering for Recommending Movies
Bøe, Cecilie (Master thesis, 2007)There is a significant amount of ongoing research in the collaborative filtering field, with much of the research focusing on how to most accurately give item predictions to a user, based on ratings given by other users ... -
Comparative Study of Event Prediction in Power Grids using Supervised Machine Learning Methods
Høiem, Kristian Wang; Santi, Vemund Mehl; Torsæter, Bendik Nybakk; Langseth, Helge; Andresen, Christian Andre; Rosenlund, Gjert Hovland (Chapter, 2020)There is a growing interest in applying machine learning methods on large amounts of data to solve complex problems, such as prediction of events and disturbances in the power system. This paper is a comparative study of ... -
Computing in Unstructured Matter
Lykkebø, Odd Rune S. (Doctoral theses at NTNU;2017:90, Doctoral thesis, 2017) -
Correcting Classification: A Bayesian Framework Using Explanation Feedback to Improve Classification Abilities
Bekkemoen, Yanzhe (Master thesis, 2021)Nevrale nettverk (NNs) har vist høy prediktiv ytelse, men med mangler. For det første er ikke årsakene bak klassifiseringene fullstendig forstått. Flere forklaringsmetoder er utviklet, men de har ikke mekanismer for brukere ... -
Data driven case base construction for prediction of success of marine operations
Mathisen, Bjørn Magnus; Aamodt, Agnar; Langseth, Helge (Journal article; Peer reviewed, 2017)It is a common situation to have lots of recorded data that you want to use for improving a process in your organization or make use of this data to provide new services or products. Starting with one primary data set we ... -
Data Driven Protein Structure Prediction: Development of a SAXS ab initio modeling in a probabilistic inference framework
Andreetta, Christian (Master thesis, 2008)Protein structure prediction is one of the most interesting and researched targets in computational biology. The problem in itself is easily posed: to model the three-dimensional structure of a protein, given its genetic ... -
Data mining methods for the analysis of power systems of vessels
Swider, Anna (Doctoral theses at NTNU;2018:412, Doctoral thesis, 2018)Measurements from on-board monitoring systems of vessels are now increasingly available for data analysis, and their relevance is growing as the ship industry enters the digitilization phase. The analysis of data from ... -
Decision Support for Predictive Maintenance of Exposed Aquaculture Structures
Pedersen, Niklas Bae; Roppestad, Fredrik Lindahl (Master thesis, 2016)It is a global challenge to produce enough healthy food to a growing world population. By moving industrial fish farming to exposed lo- cations, the farmers can possibly satisfy the dietary requirements of the future by ... -
Decision support in patient-centered health care
Prestmo, Tale (Master thesis, 2017)This thesis aims to create exercise plans for patients with low back pain and is a part of the research project selfBACK. Case-based reasoning is used to create the exercise plans, which is the process of solving new ... -
Decoupling deep learning and reinforcement learning for stable and efficient deep policy gradient algorithms
Clemente, Alfredo Vicente (Master thesis, 2017)This thesis explores the exciting new field of deep reinforcement learning (Deep RL). This field combines well known reinforcement learning algorithms with newly developed deep learning algorithms. With Deep RL it is ... -
Deep Contextual Grid Triplet Network for Context-Aware Recommendation
Aftab, Sofia; Ramampiaro, Heri; Langseth, Helge; Ruocco, Massimiliano (Peer reviewed; Journal article, 2023)Modeling contextual information is a vital part of developing effective recommender systems. Still, existing work on recommendation algorithms has generally put limited focus on the effective treatment of contextual ... -
Design of a Bayesian Recommender System for Tourists Presenting a Solution to the Cold-Start User Problem
Lillegraven, Terje Nesbakken; Wolden, Arnt Christian (Master thesis, 2010)Recommender systems aim to provide users with personalised recommendations of items based on their preferences. Such systems have during the last 15 years been applied in many domains and have enjoyed an increased popularity ... -
Design of a Hybrid Recommender System: A Study of the Cold-Start User Problem
Lund, Sigurd Støen; Tandberg, Øystein (Master thesis, 2015)Recommender systems are used to help users discover the items they might be interested in, especially when the number of alternatives is big. In modern streaming websites for music, movies, and TV-shows, E-commerce, social ... -
Detection of Potential Manipulations in Electricity Market using Machine Learning Approaches
Tiwari, Shweta; Bell, Gavin; Langseth, Helge; Ramampiaro, Heri (Peer reviewed; Journal article, 2022)Detecting potential manipulations by monitoring trading activities in the electricity market is a time- consuming and challenging task despite the involvement of experienced market surveillance experts. This is due to the ... -
Early Warnings of Corporate Bankruptcies Using Machine Learning Techniques
Gogstad, Jostein; Øysæd, Jostein (Master thesis, 2009)The tax history of a company is used to predict corporate bankruptcies using Bayesian inference. Our developed model uses a combination of Naive Bayesian classification and Gaussian Processes. Based on a sample of 1184 ...