Blar i Publikasjoner fra CRIStin - NTNU på tittel
Viser treff 7661-7680 av 37384
-
Data-driven energy management of isolated power systems under rapidly varying operating conditions
(Peer reviewed; Journal article, 2022)We propose an energy management algorithm for isolated industrial power systems that integrate uncertain renewable generation and energy storage. The proposed strategy is designed to ensure sustainable and cost-effective ... -
A Data-driven Explainable Case-based Reasoning Approach for Financial Risk Detection
(Peer reviewed; Journal article, 2022)The rapid development of artificial intelligence methods contributes to their wide applications for forecasting various financial risks in recent years. This study introduces a novel explainable case-based reasoning (CBR) ... -
Data-driven information for action
(Journal article; Peer reviewed, 2023)Because of the increase in data and the possibilities created by machine learning, organizations are now looking to become more data-driven. In sociotechnical systems design there has been a focus on designing information ... -
Data-driven Intrusion Detection System for Small and Medium Enterprises
(Journal article; Peer reviewed, 2019)Small and Medium Enterprises (SMEs) have become targets of attack by cyber criminals in resent times. This paper therefore aim to address awareness and challenges of SMEs related to IDSs as the most important defense tool ... -
Data-Driven Machine Learning Approach for Human Action Recognition Using Skeleton and Optical Flow
(Chapter, 2021)Human action recognition is a very challenging problem due to numerous variations in each body part. In this paper, we propose a method for extracting optical flow information from skeleton data to address the problem of ... -
Data-driven Machine Learning Model in District Heating System for Heat Load Prediction: A Comparison Study
(Journal article; Peer reviewed, 2016)We present our data-driven supervised machine-learning (ML) model to predict heat load for buildings in a district heating system (DHS). Even though ML has been used as an approach to heat load prediction in literature, ... -
Data-Driven Maritime Processes Management Using Executable Models
(Journal article, 2018)In this paper we describe a decision support system for maritime traffic and operations, based on formal models and driven by data from the environment. To handle the complexity of system description, we work with a ... -
Data-Driven Methodology for the Analysis of Operational Profile and the Quantification of Electrical Power Variability on Marine Vessels
(Journal article; Peer reviewed, 2018)Measurements from the on-board systems of marine vessels are increasingly available for data analysis and are growing in importance as the ship industry enters a phase of digitalization. The purposes of the data analysis ... -
A Data-Driven Model for Ice-Breaking Resistance of Structure Based on Non-Smooth Discrete Element Method and Artificial Neural Network Method
(Peer reviewed; Journal article, 2023)In this paper, a data-driven model based on the Non-smooth Discrete Element Method (NDEM) and Artificial Neural Network Method (ANN) is proposed for the computation of the ice-breaking resistance of the structure. The idea ... -
Data-driven modeling of a CO2 refrigeration system
(Peer reviewed; Journal article, 2019)This paper describes a data-driven method for system identification of a CO 2 refrigeration system. Traditionally, the interaction between the measured variables is not utilized as they are highly dependent on the refrigeration ... -
Data-driven modeling of fatigue effects following repeated muscular contractions
(Chapter, 2022)We propose a novel dynamical model for describing muscular fatigue and cramping following repeated muscular contractions in the case of female Kegel exercising. The proposed compartmental model adds opportune parameters ... -
Data-driven modeling of fatigue effects following repeated muscular contractions
(Chapter, 2022)We propose a novel dynamical model for describing muscular fatigue and cramping following repeated muscular contractions in the case of female Kegel exercising. The proposed compartmental model adds opportune parameters ... -
Data-driven modeling of hydrodynamic loading using NARX and harmonic probing
(Peer reviewed; Journal article, 2023)Optimizing floating wind turbines and their mooring systems requires validated computational models that predict wave-frequency and low-frequency hydrodynamic loads. Low-frequency loads are crucial for determining extreme ... -
Data-driven Modeling of Ship Motion Prediction Based on Support Vector Regression
(Journal article; Peer reviewed, 2017)This paper presents a flexible system structure to analyze and model for the potential use of huge ship sensor data to generate efficient ship motion prediction model. The noisy raw data is cleaned using noise reduction, ... -
Data-driven modelling of a R744 refrigeration system with parallel compression configuration
(Chapter, 2019)The type and characteristics of the employed components, subsystems and refrigerant in a commercial refrigeration system varies significantly depending on required functionalities (e.g. MT (medium temperature), LT (low ... -
Data-driven models of pelvic floor muscles dynamics subject to psychological and physiological stimuli
(Journal article; Peer reviewed, 2019)This paper proposes individualized, dynamical and data-driven models to describe pelvic floor muscle responses in women undergoing vaginal dilation. Specifically, the models describe how the aggregated pressure exerted by ... -
Data-Driven Personalized Cervical Cancer Risk Prediction: A Graph-Perspective
(Chapter, 2021)Routine cervical cancer screening at regular periodic intervals leads to either over-screening or too infrequent screening of patients. For this purpose, personalized screening intervals are desirable that account for ... -
Data-driven prediction of mean wind turbulence from topographic data
(Peer reviewed; Journal article, 2021)This study presents a data-driven model to predict mean turbulence intensities at desired generic locations, for all wind directions. The model, a multilayer perceptron, requires only information about the local topography ... -
Data-Driven Prediction of Ship Propulsion Power Using Spark Parallel Random Forest on Comprehensive Ship Operation Data
(Chapter, 2022)This paper aims to propose an efficient machine learning framework for maritime big data and use it to train a random forest model to estimate ships’ propulsion power based on ship operation data. The comprehensive data ... -
Data-Driven Prediction of Vortex-Induced Vibration Response of Marine Risers Subjected to Three-Dimensional Current
(Chapter, 2019)Slender marine structures such as deep-water marine risers are subjected to currents and will normally experience Vortex Induced Vibrations (VIV), which can cause fast accumulation of fatigue damage. The ocean current is ...