Sökning: "anomaly-detection algorithm"
Visar resultat 1 - 5 av 72 uppsatser innehållade orden anomaly-detection algorithm.
1. Log Frequency Analysis for Anomaly Detection in Cloud Environments
Master-uppsats, Blekinge Tekniska Högskola/Institutionen för programvaruteknikSammanfattning : Background: Log analysis has been proven to be highly beneficial in monitoring system behaviour, detecting errors and anomalies, and predicting future trends in systems and applications. However, with continuous evolution of these systems and applications, the amount of log data generated on a timely basis is increasing rapidly. LÄS MER
2. DISTRIBUTED ARTIFICIAL INTELLIGENCE FOR ANOMALY DETECTION IN A MODULAR MANUFACTURING ENVIRONMENT
Magister-uppsats, Mälardalens universitet/Akademin för innovation, design och teknikSammanfattning : This thesis investigates anomaly detection and classification in a simulated modular manufacturingenvironment using Machine Learning algorithm Random Forest. This algorithm is tested on a localcomputer and an embedded device, specifically the Raspberry PI. LÄS MER
3. Anomaly Detection for Condition Monitoring in Robot Systems
Master-uppsats, Uppsala universitet/Institutionen för informationsteknologiSammanfattning : This thesis addresses the detection of wear patterns in robot joints as an indication of the increase in wear level or impending failures. The main challenges include identifying key wear features, developing efficient anomaly detection algorithms, ensuring generalization across different joints and operating conditions, and enabling real-time monitoring. LÄS MER
4. Anomaly Detection for Network Traffic in a Resource Constrained Environment
Master-uppsats, Mälardalens universitet/Akademin för innovation, design och teknikSammanfattning : Networks connected to the internet are under a constant threat of attacks. To protect against such threats, new techniques utilising already connected hardware have in this thesis been proven to be a viable solution. LÄS MER
5. Finding Causal Relationships Among Metrics In A Cloud-Native Environment
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Automatic Root Cause Analysis (RCA) systems aim to streamline the process of identifying the underlying cause of software failures in complex cloud-native environments. These systems employ graph-like structures to represent causal relationships between different components of a software application. LÄS MER