Blar i NTNU Open på tittel
Viser treff 56337-56356 av 100943
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Machine Learning for Spatio-Temporal Forecasting of Ambulance Demand: A Norwegian Case Study
(Master thesis, 2021)I akuttmedisinen opererer man ofte i en kamp mot klokken. Man må fordele tilgjengelige ressurser strategisk slik at man kan nå mennesker i nød på kortest mulig tid og redde liv. For å kunne posisjonere ambulanser strategisk ... -
Machine learning for surge modeling
(Master thesis, 2022)Den norske petroleumsindustrien er ikke bare en Norges største inntektskilder, men den er også en av verdens størse gass- og oljeleverandører i det globale markedet. Equinor opplever variasjoner i væskerate på topside (et ... -
Machine Learning in Financial Market Surveillance: A Survey
(Peer reviewed; Journal article, 2021)The use of machine learning for anomaly detection is a well-studied topic within various application domains. However, the detection problem for market surveillance remains challenging due to the lack of labeled data and ... -
Machine Learning in Predictive Maintenance of Railway Infrastructures: Implementations and Challenges
(Master thesis, 2022)De nylige teknologiske fremskrittene av Industry 4.0 teknologier har skapt et skifte mot applikasjoner innen maskinlæring (ML) for prediktivt vedlikehold (PdM) og har blitt tatt i bruk av mange bransjer. Derimot finnes det ... -
Machine learning in robotics: Explaining autonomous agents in real time
(Doctoral theses at NTNU;2023:134, Doctoral thesis, 2023)Artifcial intelligence (AI) and machine learning (ML) offer a number of benefits in multiple applications within the field of robotics, such as computer vision, object grasping, motion control, and planning. Although AI ... -
Machine learning meets continuous flow chemistry: Automated optimization towards the Pareto front of multiple objectives
(Journal article; Peer reviewed, 2018)Automated development of chemical processes requires access to sophisticated algorithms for multi-objective optimization, since single-objective optimization fails to identify the trade-offs between conflicting performance ... -
Machine Learning Methods for Anomaly Detection on Phasor Measurement Unit Data
(Master thesis, 2022)I en verden av økende digitalisering, kombinert med en økende etterspørsel etter strøm fra rene energikilder, vokser den cyber-fysiske interaksjonen i kraftsystemet stadig fortere. Denne veksten krever nye og bedre teknikker ... -
Machine Learning Methods for Anomaly Detection on Phasor Measurement Unit Data
(Master thesis, 2022)I en verden av økende digitalisering, kombinert med en økende etterspørsel etter strøm fra rene energikilder, vokser den cyber-fysiske interaksjonen i kraftsystemet stadig fortere. Denne veksten krever nye og bedre teknikker ... -
Machine Learning Methods for Bathymetry Generation in Rivers
(Master thesis, 2022)Natural flood hazards resulted in more than 500,000 reported deaths during the last 20 years. This number is expected to increase in the future due to population growth, rapid urbanization and increased rainfall intensities ... -
Machine learning methods for prediction of hot water demands in integrated R744 system for hotels
(Chapter, 2020)Load forecasting can help modern energy systems achieve more efficient operation by means of more accurate peak power shaving and more reliable control. This paper proposes a framework based on machine learning algorithms ... -
Machine learning methods for sleep-wake classification using two body-worn accelerometers
(Master thesis, 2019)Søvn er en viktig faktor for beskytte en persons fysiske og mentale trivsel. Derfor utføres mange studier som fokuserer på forebygge, diagnostisere og behandle søvnforstyrrelser. En avgjørende del av disse studiene er ... -
Machine Learning Modelling of the Oxidative and Thermal Degradation of Monoethanolamine (MEA)
(Master thesis, 2021)Folketallet i verden vokser, noe som fører til en økning i forbruket av ressurser og utslipp av klimagasser. Som et resultat av dette øker konsentrasjonene av klimagasser i atmosfæren til farlige nivåer, og behovet for ... -
Machine Learning of Circulatory Oscillations in Cardiac Surgical Patients
(Master thesis, 2016)The human circulatory system is a complex organ system, with multiple feedback and feedforward mechanism for regulation. When global circulatory variables are assessed, these exhibit distinct oscillatory patterns with ... -
Machine Learning of Infant Spontaneous Movements for the Early Prediction of Cerebral Palsy: A Multi-Site Cohort Study
(Journal article; Peer reviewed, 2019)Background: Early identification of cerebral palsy (CP) during infancy will provide opportunities for early therapies and treatments. The aim of the present study was to present a novel machine-learning model, the ... -
Machine Learning of Quality Assurance in Polymer Powder Bed Fusion Additive Manufacturing
(Doctoral theses at NTNU;2020:120, Doctoral thesis, 2020)The latest developments in the field of additive manufacturing (AM) have led to the wider use of this technology for the production of end-user products. As a result, more stringent requirements are set to the quality of ... -
Machine Learning of Sub-Phonemic Units for Speech Recognition
(Master thesis, 2015)This work is intended to explore the performance of a new set of acoustic model units in speech recognition. The acoustic models were built and evaluated from scratch in several steps: Feature extraction, acoustic detection ... -
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 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 ...