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Data set for power system reliability analysis using a four-area test network
(Peer reviewed; Journal article, 2020)This article presents a test data set combining data relevant for power system reliability analysis, including network data, reliability data, basic interruption cost data, and exemplary operating state data. The data set ... -
A data set of a Norwegian energy community
(Peer reviewed; Journal article, 2021)This paper presents a data set designed to represent Norwegian energy communities. As such it includes household consumption data collected from smart meter measurements and divided into consumer groups, appliance consumption ... -
The Data Value Quest: A Holistic Semantic Approach at Bosch
(Peer reviewed; Journal article, 2022) -
Data-based calibration of physics-based thermal models of single-family houses
(SINTEF Proceedings;5, Chapter; Peer reviewed, 2020)The calibration of building energy simulation models is crucial for addressing the issue of the discrepancy between the simulation output and real-world measurements. The majority of current research studies have used ... -
A data-driven approach for twitter hashtag recommendation
(Peer reviewed; Journal article, 2020)This paper addresses the hashtag recommendation problem using high average-utility pattern mining. We introduce a novel framework called PM-HRec (Pattern Mining for Hashtag Recommendation). It consists of two main stages. ... -
A Data-Driven Approach for Twitter Hashtag Recommendation
(Peer reviewed; Journal article, 2020)This paper addresses the hashtag recommendation problem using high average-utility pattern mining. We introduce a novel framework called PM-HRec (Pattern Mining for Hashtag Recommendation). It consists of two main stages. ... -
Data-driven asset management in urban water pipe networks: a proposed conceptual framework
(Peer reviewed; Journal article, 2021)Analytical tools used in infrastructure asset management of urban water pipe networks are reliant on asset data. Traditionally, data required by analytical tools has not been collected by most water utilities because it ... -
Data-driven deconvolution for large eddy simulations of Kraichnan turbulence
(Journal article; Peer reviewed, 2018)In this article, we demonstrate the use of artificial neural networks as optimal maps which are utilized for convolution and deconvolution of coarse-grained fields to account for sub-grid scale turbulence effects. We ... -
Data-driven Household Load Flexibility Modelling: Shiftable Atomic Load
(Chapter; Peer reviewed, 2018)To keep a stable power system, there should always be balance between the generation and consumption of electricity. In this study, a flexibility modelling method for atomic loads which is based on high resolution appliance ... -
Data-driven modelling with coarse-grid network models
(Peer reviewed; Journal article, 2023)We propose to use a conventional simulator, formulated on the topology of a coarse volumetric 3D grid, as a data-driven network model that seeks to reproduce observed and predict future well responses. The conceptual ... -
Data-driven quasi-interpolant spline surfaces for point cloud approximation
(Peer reviewed; Journal article, 2020)In this paper we investigate a local surface approximation, the Weighted Quasi Interpolant Spline Approximation (wQISA), specifically designed for large and noisy point clouds. We briefly describe the properties of the ... -
Data-driven quasi-interpolant spline surfaces for point cloud approximation
(Peer reviewed; Journal article, 2020)In this paper we investigate a local surface approximation, the Weighted Quasi Interpolant Spline Approximation (wQISA), specifically designed for large and noisy point clouds. We briefly describe the properties of the ... -
Data-driven sea state estimation for vessels using multi-domain features from motion responses
(Chapter; Peer reviewed, 2021)Situation awareness is of great importance for autonomous ships. One key aspect is to estimate the sea state in a real-time manner. Considering the ship as a large wave buoy, the sea state can be estimated from motion ... -
DataBio Deliverable D4.4 – Service Documentation
(H2020 732064;D4.4, Research report, 2019-12)The public deliverable D4.4 describes the software components and processes (here called pipelines as the processes mostly consist of Big Data volumes streaming through successive processing steps) to be utilized by the ... -
DataCloud: Enabling the Big Data Pipelines on the Computing Continuum
(Chapter, 2021) -
Datadrevet oppvarming reduserer energibruken i bygg
(Journal article, 2023)Ved å forutsi det faktiske oppvarmingsbehovet i et bygg kan man spare mye energi. -
DataGraft beta v2: New features and capabilities
(Journal article; Peer reviewed, 2017)In this demonstrator, we will introduce the latest features and capabil-ities added to DataGraft – a Data-as-a-Service platform for data preparation and knowledge graph generation. DataGraft provides data transformation, ... -
DataGraft: A Platform for Open Data Publishing
(Journal article; Peer reviewed, 2016)DataGraft is a platform for Open Data management. It has the goals to simplify and speed up the data publishing process and to improve the reliability and scalability of the data consumption process. This demonstrator ... -
Datakilder og medellering av trengsel på tog
(SINTEF Rapport;A25833, Research report, 2014) -
Datakvalitet ved digitalisering i petroleumssektoren
(SINTEF Rapport;2021:00053, Research report, 2021)Formålet med denne rapporten er å undersøke hvilke datakilder og data som benyttes i industrielle IKT-systemer og hvordan data behandles og prosesseres før de gjøres tilgjengelig i kontornettet. Styrker og sårbarheter ...