Sökning: "Adaptive learning systems"

Visar resultat 1 - 5 av 61 uppsatser innehållade orden Adaptive learning systems.

1. 1. Dealing With The Unexpected in Prehospital Patientcare: The Lived Experience Of EMS Clinicians

   Magister-uppsats, Lunds universitet/Avdelningen för Riskhantering och Samhällssäkerhet

   Författare :Aart-Jan Ketelaar; [2024]
   Nyckelord :Patient safety; Prehospital patientcare; EMS clinician; Resilient healthcare; Human factors; Decision making; Learning; Expertise; Emergency care; Adapting; Complexity; Complex systems; Phenomenology; FLMU06; Social Sciences;

   Sammanfattning : Background In prehospital patient care, numerous patients are examined, treated, and transported. Some are acutely seriously ill, while others, though not acutely ill, necessitate ambulance transport due to their inability to do so independently. Among the latter group, patients may be sicker than initially estimated. LÄS MER

3. 2. Unsupervised Online Anomaly Detection in Multivariate Time-Series

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Datorteknik

   Författare :Ludvig Segerholm; [2023]
   Nyckelord :unsupervised; online; anomaly detection; explainable ai; machine learning; mahalanobis distance;

   Sammanfattning : This research aims to identify a method for unsupervised online anomaly detection in multivariate time series in dynamic systems in general and on the case study of Devwards IoT-system in particular. A requirement of the solution is its explainability, online learning and low computational expense. LÄS MER

4. 3. Comparison of Recommendation Systems for Auto-scaling in the Cloud Environment

   Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Sai Nikhil Boyapati; [2023]
   Nyckelord :Auto-Scaling; Auto-Scaling Recommendations; Cloud Environment; K-Nearest Neighbors; Machine Learning; Recommendation Systems; Random Forests; Support Vector Machines;

   Sammanfattning : Background: Cloud computing’s rapid growth has highlighted the need for efficientresource allocation. While cloud platforms offer scalability and cost-effectiveness for a variety of applications, managing resources to match dynamic workloads remains a challenge. LÄS MER

5. 4. 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. 5. Evolutionary Belief Rule based Explainable AI to Predict Air Pollution

   Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Sharif Noor Zisad; [2023]
   Nyckelord :Explainable AI; Explainability; Transparency; Belief Rule Based Expert System; Evolutionary Algorithm; Deep Learning;

   Sammanfattning : This thesis presents a novel approach to make Artificial Intelligence (AI) more explainable by using a Belief Rule Based Expert System (BRBES). A BRBES is a type of expert system that can handle both qualitative and quantitative information under uncertainty and incompleteness by using if-then rules with belief degrees. LÄS MER