Blar i Fakultet for informasjonsteknologi og elektroteknikk (IE) på tittel
Viser treff 11148-11167 av 20210
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Machine Learning for Smart Building Applications: Review and Taxonomy
(Journal article; Peer reviewed, 2019)The use of machine learning (ML) in smart building applications is reviewed in this article. We split existing solutions into two main classes: occupant-centric versus energy/devices-centric. The first class groups solutions ... -
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 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 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 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 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 ... -
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 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 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 ... -
Machine vision for quality sorting of salmonid fish eggs
(Master thesis, 2020)I fiskeoppdrett er kvalitetskontroll og fjerning av døde fiskeegg, også omtalt som rogn, første steg i produksjonsprosessen. Mengden av rogn som overlever dette stadiet og vokser til fiskeyngel er tungt knyttet til hvor ... -
Machine-Checked Proofs of Privacy Against Malicious Boards for Selene & Co
(Chapter, 2022)Privacy is a notoriously difficult property to achieve in complicated systems and especially in electronic voting schemes. Moreover, electronic voting schemes is a class of systems that require very high assurance. The ... -
Machine-learning algorithms for the computation of upscaled permeabilities
(Master thesis, 2018)In full-scale reservoir simulation models, the characteristics of the rock are not fully resolved. Upscaled permeabilities are used to account for the effective behaviour of a composite region. By averaging the fine ...