Blar i NTNU Open på tittel
Viser treff 56318-56337 av 100872
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Machine Learning on Complex Projects: Multivariate time series data analysis through utilization of the sequential algorithm LSTM
(Master thesis, 2021)Bruken av maskinlæring har vokst kraftig i løpet av de siste tiårene, og de mange suksesshistoriene har kastet lys over dens iboende verdi. Flere av disse suksesshistoriene stammer fra selskaper som allerede er i den ... -
Machine learning procedures for automatic well planning in reservoir simulation models
(Doctoral theses at NTNU;2021:404, Doctoral thesis, 2021)Simulation of reservoir models is a tool to optimize the development of an oil and gas reservoir. Part of the development is placement of wells in the reservoir, and this well placement optimization process is performed ... -
Machine learning techniques for modeling chemical absorption in CO2 capture process
(Chapter, 2022)Post-combustion carbon capture (PCC) technologies play an important role in the reduction of CO2 emissions to address climate challenges. This process is usually simulated in process simulation software based on first-principle ... -
Machine learning techniques for real-time collision detection in a wheeled mobile robot
(Master thesis, 2023)This thesis focuses on the application of various machine learning (ML) techniques to improve the overall dependability of a wheeled mobile robot (WMR) control during a real-time simulation. The whole system consists on a ... -
Machine Learning using High Resolution Zivid Point Clouds on a High Performance Cluster
(Master thesis, 2022)I dette masterprosjektet presenteres det metoder og arbeid som muligjør bruken av høyoppløste Zivid punktskyer i maskinlæringsbiblioteket Minkowski Engine skrevet av Chris Choy. I tillegg har det blitt laget et datasett ... -
Machine learning-based estimation of buildings' characteristics employing electrical and chilled water consumption data: Pipeline optimization
(Peer reviewed; Journal article, 2023)Smart meter-driven remote auditing of buildings, as an alternative to the labor-intensive on-site visits, permits large-scale and rapid identification of buildings with low energy performance. The existing literature has ... -
Machine learning-based immune phenotypes correlate with STK11/KEAP1 co-mutations and prognosis in resectable NSCLC: a sub-study of the TNM-I trial
(Peer reviewed; Journal article, 2023)Background We aim to implement an immune cell score model in routine clinical practice for resected non-small-cell lung cancer (NSCLC) patients (NCT03299478 ). Molecular and genomic features associated with immune ... -
A Machine Learning-Based Model for Stability Prediction of Decentralized Power Grid Linked with Renewable Energy Resources
(Peer reviewed; Journal article, 2022)A decentralized power grid is a modern system that implements demand response without requiring major infrastructure changes. In decentralization, the consumers regulate their electricity demand autonomously based on the ... -
Machine Learning-based Occupancy Estimation Using Multivariate Sensor Nodes
(Chapter, 2019)In buildings, a large chunk of energy is spent on heating, ventilation and air conditioning systems. One way to optimize their usage is to make them demand-driven depending on human occupancy. This paper focuses on accurately ... -
Machine learning-based predictive maintenance: A cost-oriented model for implementation
(Journal article; Peer reviewed, 2021)Predictive Maintenance (PdM) is a condition-based maintenance strategy (CBM) that carries out maintenance action when needed, avoiding unnecessary preventive actions or failures. Machine learning (ML), in the form of ... -
Machine Learning-based Time Series Forecasting for Dynamic Reorder Points
(Master thesis, 2023)Etterspørselen etter helsetjenester i Norge øker på grunn av demografiske endringer, inkludert en voksende og aldrende befolkning. Denne økningen i etterspørsel forventes å føre til høyere helseutgifter og øke presset på ... -
Machine Learning-based Time Series Forecasting for Dynamic Reorder Points
(Master thesis, 2023)Etterspørselen etter helsetjenester i Norge øker på grunn av demografiske endringer, inkludert en voksende og aldrende befolkning. Denne økningen i etterspørsel forventes å føre til høyere helseutgifter og øke presset på ... -
Machine Learning-based Uptime-Prediction for Battery-friendly Passenger Information Displays
(Chapter, 2020)Personal Information Displays (PID) at bus stops help making the usage of public transport more attractive. If no electric grid is nearby, however, the installation of PIDs is very expensive due to the high wiring costs. ... -
Machine Learning-Enabled Predictive Modeling of Building Performance for Electricity Optimization
(Master thesis, 2023)Med den raske fremgangen i maskinlæring har prediktiv modellering dukket opp som en attraktiv metode for å optimalisere energibruk, også innen bygningssektoren. Denne avhandlingen utforsker ulike modelleringsparadigmer for ... -
Machine learning-guided design of lattice structures
(Master thesis, 2023)For decades, scientists and engineers have been striving to develop materials that are both light-weight and strong, stable, and resilient, with applications ranging from aerospace to the biomedical industry. While ... -
Machine learning: A useful tool in geomechanical studies, a case study from an offshore gas field
(Peer reviewed; Journal article, 2020)For a safe drilling operation with the of minimum borehole instability challenges, building a mechanical earth model (MEM) has proven to be extremely valuable. However, the natural complexity of reservoirs along with the ... -
Machine prescription for chronic migraine
(Peer reviewed; Journal article, 2022)Responsive to treatment individually, chronic migraine remains strikingly resistant collectively, incurring the second-highest population burden of disability worldwide. A heterogeneity of responsiveness, requiring ... -
Machine prescription for chronic migraine
(Peer reviewed; Journal article, 2022)Responsive to treatment individually, chronic migraine remains strikingly resistant collectively, incurring the second-highest population burden of disability worldwide. A heterogeneity of responsiveness, requiring ... -
Machine Translation in Low-Resource Languages by an Adversarial Neural Network
(Peer reviewed; Journal article, 2021)Existing Sequence-to-Sequence (Seq2Seq) Neural Machine Translation (NMT) shows strong capability with High-Resource Languages (HRLs). However, this approach poses serious challenges when processing Low-Resource Languages ... -
Machine Vision for Defect Detection in Fisheries and Fish Processing Applications
(Doktoravhandlinger ved NTNU, 1503-8181; 2009:203, Doctoral thesis, 2009)The fisheries and fish processing industries have high labor costs. In part, this is due to visual inspection tasks, which are found in these industries, being so complex that humans are needed to do the inspection. One ...