Sökning: "Adaptive learning systems"
Visar resultat 1 - 5 av 61 uppsatser innehållade orden Adaptive learning systems.
1. Dealing With The Unexpected in Prehospital Patientcare: The Lived Experience Of EMS Clinicians
Magister-uppsats, Lunds universitet/Avdelningen för Riskhantering och SamhällssäkerhetSammanfattning : 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
2. Unsupervised Online Anomaly Detection in Multivariate Time-Series
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/DatorteknikSammanfattning : 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
3. Comparison of Recommendation Systems for Auto-scaling in the Cloud Environment
Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskapSammanfattning : 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
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)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
5. Evolutionary Belief Rule based Explainable AI to Predict Air Pollution
Master-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknikSammanfattning : 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
![](http://www.uppsatser.se/graphics/blank.gif)