Zerrendatu honen arabera: gaia "machine learning"
12-tik 1-12 emaitza erakusten
-
Aging Modulates the Resting Brain after a Memory Task: A Validation Study from Multivariate Models
(MDPI AG, 2019)Recent work has demonstrated that aging modulates the resting brain. However, the study of these modulations after cognitive practice, resulting from a memory task, has been scarce. This work aims at examining age-related ... -
Best Practice Data Sharing Guidelines for Wind Turbine Fault Detection Model Evaluation
(MDPI, 2023)In this paper, a set of best practice data sharing guidelines for wind turbine fault detection model evaluation is developed, which can help practitioners overcome the main challenges of digitalisation. Digitalisation is ... -
Calendar Ageing Model for Li-Ion Batteries Using Transfer Learning Methods
(MDPI, 2021)Getting accurate lifetime predictions for a particular cell chemistry remains a challenging process, largely dependent on time and cost-intensive experimental battery testing. This paper proposes a transfer learning (TL) ... -
Data‐Driven Low‐Frequency Oscillation Event Detection Strategy for Railway Electrification Networks
(MDPI, 2023)Low-frequency oscillations (LFO) occur in railway electrification systems due to the incorporation of new trains with switching converters. As a result, the increased harmonic content can cause catenary stability problems ... -
Development and Comparison of Rule- and Machine Learning-Based EMS for HESS Providing Grid Services
(IEEE, 2024)In this paper, a smart machine-learning-based energy management system (MLBEMS) is developed for a hybrid energy storage system (HESS). This HBESS consists of batteries with high-energy (HE) and high-power (HP) characteristics, ... -
Goal-Conditioned Reinforcement Learning within a Human-Robot Disassembly Environment
(MDPI, 2022)The introduction of collaborative robots in industrial environments reinforces the need to provide these robots with better cognition to accomplish their tasks while fostering worker safety without entering into safety ... -
Gotham Testbed: A Reproducible IoT Testbed for Security Experiments and Dataset Generation
(IEEE, 2023)The growing adoption of the Internet of Things (IoT) has brought a significant increase in attacks targeting those devices. Machine learning (ML) methods have shown promising results for intrusion detection; however, the ... -
Identification of the Parameter Values of the Constitutive and Friction Models in Machining Using EGO Algorithm: Application to Ti6Al4V
(MDPI, 2022)The application of artificial intelligence and increasing high-speed computational performance is still not fully explored in the field of numerical modeling and simulation of machining processes. The efficiency of the ... -
Incorporation of Synthetic Data Generation Techniques within a Controlled Data Processing Workflow in the Health and Wellbeing Domain
(MDPI, 2022)To date, the use of synthetic data generation techniques in the health and wellbeing domain has been mainly limited to research activities. Although several open source and commercial packages have been released, they have ... -
Machine Learning-Based Fault Detection and Diagnosis of Faulty Power Connections of Induction Machines
(MDPI, 2021)Induction machines have been key components in the industrial sector for decades, owing to different characteristics such as their simplicity, robustness, high energy efficiency and reliability. However, due to the stress ... -
A novel machine learning‐based methodology for tool wear prediction using acoustic emission signals
(MDPI, 2021)There is an increasing trend in the industry of knowing in real-time the condition of their assets. In particular, tool wear is a critical aspect, which requires real-time monitoring to reduce costs and scrap in machining ... -
Validation of Random Forest Machine Learning Models to Predict Dementia-Related Neuropsychiatric Symptoms in Real-World Data
(IOS Press, 2020)Background: Neuropsychiatric symptoms (NPS) are the leading cause of the social burden of dementia but their role is underestimated. Objective: The objective of the study was to validate predictive models to separately ...
