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Universitetet i Stavanger [18538]
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Assessing Impact of Borehole Field Data’s Input Parameters on Hybrid Deep Learning Models for Heating and Cooling Forecasting: A Local and Global Explainable AI Analysis
(Peer reviewed; Journal article, 2023)Achieving accurate performance forecasting of borehole heat exchanger is essential for optimizing ground source heat pump systems, enabling optimal control, and facilitating energy-efficient operations with enhanced ... -
An image processing approach to reconstruct wind using long-range wind lidars
(Peer reviewed; Journal article, 2023)Lidar-based wind sensing technology, originally used in the wind energy sector, is now being utilized in wind engineering to monitor wind action for designing fjord-crossing infrastructure like long-span bridges. Accurate ... -
Heart rate and QRS duration as biomarkers predict the immediate outcome from pulseless electrical activity
(Peer reviewed; Journal article, 2023)Introduction Pulseless electrical activity (PEA) is commonly observed in in-hospital cardiac arrest (IHCA). Universally available ECG characteristics such as QRS duration (QRSd) and heart rate (HR) may develop differently ... -
Machine learning for underground gas storage with cushion CO2 using data from reservoir simulation
(Peer reviewed; Journal article, 2023)Underground natural gas storage (UNGS) is a means to store energy temporarily for later recovery and use. In such storage operations, carbon dioxide (CO2) can be injected as cushion gas to improve the operating efficiency ... -
Fixed type-oscillating water column front wall angle variation and impact on chamber performance: CFD numerical wave tank assessment
(Peer reviewed; Journal article, 2023)This study investigates optimizing the front wall geometry of an Oscillating Water Column (OWC) chamber to enhance turbine performance and output efficiency when harnessing energy from progressive waves with consistent ...