Sökning: "utilizing networks"

Visar resultat 21 - 25 av 231 uppsatser innehållade orden utilizing networks.

1. 21. Designing and evaluating distribution networks for luxury beds : A case study of Hästens Beds’ European distribution from the perspective of cost and delivery service

   Master-uppsats, Linköpings universitet/Logistik- och kvalitetsutveckling

   Författare :Sebastian Huss; Arvid Normann; [2023]
   Nyckelord :distribution; distribution network design; transport minimization; network structure; network optimization; decentralization; facility location; center of gravity;

   Sammanfattning : Hästens Beds is a Swedish luxury bed manufacturer, located in Köping, Sweden. They have a strong global presence, with Europe being the most mature and proven market. LÄS MER

3. 22. Prediction Models for TV Case Resolution Times with Machine Learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Borja Javierre I Moyano; [2023]
   Nyckelord :Datasets; Machine Learning ML ; Prediction; Resolution Time RT ; Solve Time; TV Cases; Trouble Tickets TT ; Customer-Related Trouble Tickets Resolution Time; CRM system; BI system; Telecommunications; Dataset; Machine Learning ML ; Prediction; Resolution Time; Solve Time; TV Cases; Trouble Tickets TT ; Kundrelaterade problem Tickets Resolution tid; CRM-system; BI-system; Telekommunikationer.;

   Sammanfattning : TV distribution and stream content delivery of video over the Internet, since is made up of complex networks including Content Delivery Networks (CDNs), cables and end-point user devices, that is very prone to issues appearing in different levels of the network ending up affecting the final customer’s TV services. When a problem affects the customer, and this prevents from having a proper TV delivery service in devices used for stream purposes, the issue is reported through a call, a TV case is opened and the company’s customer handling agents start supervising it to solve the problem as soon as possible. LÄS MER

4. 23. Estimating eco-friendly driving behavior in various traffic situations, using machine learning

   Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

   Författare :Ludvig Fors; [2023]
   Nyckelord :Machine learning; transformers; neural networks; casual inference; K-Means; driver behavior; fuel consumption;

   Sammanfattning : This thesis investigates how various driver signals, signals that a truck driver can interact with, influences fuel consumption and what are the optimal values of these signals in various traffic conditions. More specifically, the objective is to estimate good driver behavior in various traffic conditions and compare bad driver behavior in similar situations to see how performing a specific driver action, changing a driver signal from the bad driver value to the corresponding good driver value impacts the fuel consumption. LÄS MER

5. 24. Anomaly Detection in the EtherCAT Network of a Power Station : Improving a Graph Convolutional Neural Network Framework

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Niklas Barth; [2023]
   Nyckelord :Unsupervised Learning; Multivariate Time Series; Graph Convolutional Neural Networks; Anomaly Detection; Industrial Control System; EtherCAT; Power Station; Electricity Grid;

   Sammanfattning : In this thesis, an anomaly detection framework is assessed and fine-tuned to detect and explain anomalies in a power station, where EtherCAT, an Industrial Control System, is employed for monitoring. The chosen framework is based on a previously published Graph Neural Network (GNN) model, utilizing attention mechanisms to capture complex relationships between diverse measurements within the EtherCAT system. LÄS MER

7. 25. Finding the QRS Complex in a Sampled ECG Signal Using AI Methods

   Master-uppsats, KTH/Fysik

   Författare :Jeanette Marie Victoria Skeppland Hole; [2023]
   Nyckelord :ECG; ECG-analysis; QRS detector; Artificial Intelligence; Machine Learning; Deep neural networks; Long short-term memory; Convolutional neural network; Multilayer perceptron; EKG; EKG-analys; QRS detektor; Artificiell intelligens; Maskininlärning; Djupa neurala nätverk; Long short-term memory; Convolutional neural network; Multilayer perceptron;

   Sammanfattning : This study aimed to explore the application of artificial intelligence (AI) and machine learning (ML) techniques in implementing a QRS detector forambulatory electrocardiography (ECG) monitoring devices. Three ML models, namely long short-term memory (LSTM), convolutional neural network (CNN), and multilayer perceptron (MLP), were compared and evaluated using the MIT-BIH arrhythmia database (MITDB) and the MIT-BIH noise stress test database (NSTDB). LÄS MER