Browsing NTNU Open by Author "Gundersen, Odd Erik"
Now showing items 21-40 of 71
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Do machine learning platforms provide out-of-the-box reproducibility?
Gundersen, Odd Erik; Shamsaliei, Saeid; Isdahl, Richard Juul (Journal article; Peer reviewed, 2021) -
Electricity Price Forecasting Benchmark of ENTCN on Nordic Bidding Areas
Bugge, Erling Stray; Wang, Tarje Rusten (Master thesis, 2022)Selv om prognoser for strømpriser har sett et mylder av foreslåtte modeller de siste tiårene, har feltet fortsatt et begrenset antall systematiske benchmarkinger. I denne oppgaven utfører vi en strukturert benchmark av et ... -
Enhancing the Situation Awareness of Decision Makers by Applying Case-Based Reasoning on Streaming Data
Gundersen, Odd Erik (Doctoral thesis at NTNU;2014:315, Doctoral thesis, 2014)Data is generally expected to continue its exponential growth the next five to ten years. However, it is commonly agreed that the amount of data that currently exist is abundant and that there is still much to achieve ... -
Evaluation of Multi-step Forecasting Models: An Empirical Deep Learning Study
Strøm, Eivind (Master thesis, 2021)Denne masteroppgaven omhandler evaluering av metoder for flerperiodeprediksjon av tidsserier ved å gjennomføre en empirisk studie med dype læringsmodeller. I dag blir modeller for flerperiodeprediksjon evaluert ved at en ... -
Examining the Effect of Implementation Factors on Deep Learning Reproducibility
Coakley, Kevin; Kirkpatrick, Christine; Gundersen, Odd Erik (Chapter, 2022)Reproducing published deep learning papers to validate their conclusions can be difficult due to sources of irreproducibility. We investigate the impact that implementation factors have on the results and how they affect ... -
Explain errors and improve timeseries forecasting models using XAI
Hossain, Md Amjad (Master thesis, 2023)Tidsserieprognoser er avgjørende for finansinstitusjoner og bransjer, og krever forskjellige modeller for forskjellige årstider og tidslinjer for å oppnå nøyaktige spådommer. Uventede feil oppstår imidlertid ofte på grunn ... -
Explaining Traffic Situations – Architecture of a Virtual Driving Instructor
Sandberg, Martin K. Hoel; Rehm, Johannes; Mnoucek, Matej; Gundersen, Odd Erik; Reshodko, Irina (Peer reviewed; Journal article, 2020)Intelligent tutoring systems become more and more common in assisting human learners. Distinct advantages of intelligent tutoring systems are personalized teaching tailored to each student, on-demand availability not ... -
Exploring Procedural Content Generation and Personalized Learning for Virtual Driving Education
Bjørnland, Fredrik; Gedde, Yrjar (Master thesis, 2023)I takt med den økte digitaliseringen i verden, har bruken av virtuelle simulatorer til pedagogiske formål blitt anerkjent og tatt i bruk i stadig økende grad. Trafikkskolen WAY har benyttet virtuelle kjøresimulatorer i ... -
Exploring Procedural Content Generation and Personalized Learning for Virtual Driving Education
Bjørnland, Johan Fredrik Rønningen; Gedde, Yrjar (Master thesis, 2023)I takt med den økte digitaliseringen i verden, har bruken av virtuelle simulatorer til pedagogiske formål blitt anerkjent og tatt i bruk i stadig økende grad. Trafikkskolen WAY har benyttet virtuelle kjøresimulatorer i ... -
The fundamental principles of reproducibility
Gundersen, Odd Erik (Peer reviewed; Journal article, 2021)Reproducibility is a confused terminology. In this paper, I take a fundamental view on reproducibility rooted in the scientific method. The scientific method is analysed and characterized in order to develop the terminology ... -
How State of Charge Impacts Machine Learning Algorithms for State of Health Estimation of Lithium-ion Batteries.
Grytten, Henrik (Master thesis, 2022)I mange applikasjoner blir bare en begrenset mengde av lithium-ion batteries utladnings kapasitet brukt. Dette gjøres for å bedre bevare helsetilstanden til batteriene. Mye av den nåværende forskningen på estimering av ... -
Implementing LOD for physically-based real-time fire rendering
Tangvald, Lars (Master thesis, 2007)In this paper, I present a framework for implementing level of detail (LOD) for a 3d physically based fire rendering running on the GPU. While realistic fire rendering that runs in real time exists, it is generally not ... -
Improving Image Quality on The Setred Scanning Slit 3D Display
Haavik, Ola (Master thesis, 2007)Human depth perception can be described trough a set of depth cues, with binocular parallax being the most important. While a 2D display can show some depth cues, only 3D displays can give binocular parallax. One type of ... -
Improving reproducibility of artificial intelligence research to increase trust and productivity
Gundersen, Odd Erik (Chapter, 2023)Several recent studies have shown that many scientific results cannot be trusted. While the “reproducibility crisis” was first recognised in psychology, the problem affects most if not all branches of science. This essay ... -
Improving the robustness of neural networks for time series forecasting through augmentationswith specific characteristics
Kjærnli, Håkon Slåtten (Master thesis, 2021)Nevrale nettverk er sett på som en toppmoderne metode i mange oppgaver som handler om mønstergjenkjenning, som bildeklassifisering og maskinoversettelse. Likevel har det blitt vist nevrale nettverk ofte produserer prediksjoner ... -
Improving User Experience of Indoor Maps Through Merging of Rooms
Normann, Morten Alver; Njærheim, Helmer Råby Schaug (Master thesis, 2017)The field of indoor map representation is an emerging field of research, contrary to outdoor maps, which has been under research for decades. A lot of focus in indoor maps has been on indoor positioning. However, map ... -
Interactive removal of outlier points in latent variable models using virtual reality
Aurstad, Tore (Master thesis, 2005)This report investigates different methods in computer graphics and virtual reality that can be applied to develop a system that provides analysis for the changes that occur when removing outlier points in plots for principal ... -
Leveraging Turbine-Level Data in a Deep Learning Approach for Wind Power Forecasting
Rommetveit, Herman; Kleppe, Lars Martin (Master thesis, 2021)Abstract will be available on 2024-06-18 -
Leveraging turbine-level data in a deep learning approach for wind power forecasting
Rommetveit, Herman; Kleppe, Lars Martin (Master thesis, 2021)Abstract will be available on 2024-06-18 -
LSTM Hybrid Model for Water Reservoir Inflow Forecasting, a Comparison Between Black Box- and Interpretable Hybrid Models
Osberg, Magnus Myrmo (Master thesis, 2020)Norges innsjøer oppnådde over 31GW innstallert vannkraftskapasitet, og produserte over 144 TWh ren kraft i 2016 i følge International Hydropower Association. Denne avhandlignen vurderer 9 hybridmodeller for prediksjon av ...