Sökning: "multivariate detection"

Visar resultat 1 - 5 av 51 uppsatser innehållade orden multivariate detection.

1. 1. Neural Network-based Anomaly Detection Models and Interpretability Methods for Multivariate Time Series Data

   Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Deepthy Prasad; Swathi Hampapura Sripada; [2023]
   Nyckelord :multivariate - time series; anomaly detection; neural networks; autoencoders; interpretability; counterfactuals;

   Sammanfattning : Anomaly detection plays a crucial role in various domains, such as transportation, cybersecurity, and industrial monitoring, where the timely identification of unusual patterns or outliers is of utmost importance. Traditional statistical techniques have limitations in handling complex and highdimensional data, which motivates the use of deep learning approaches. LÄS MER

3. 2. Preserving Privacy in Cloud Services by Using an Explainable Deep-Learning Model for Anomaly Detection

   Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

   Författare :Shiwei Dong; [2023]
   Nyckelord :;

   Sammanfattning : As cloud services become increasingly popular, ensuring their privacy and security has become a significant concern for users. Cloud computing involves Data Service Outsourcing and Computation Outsourcing, which require additional security considerations compared to traditional computing. LÄS MER

4. 3. 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

5. 4. The Application of Multivariate Statistical Process Control during Industrial Hot Isostatic Pressing Sintering Processes : A Case study at Seco Tools AB

   Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för ekonomi, teknik, konst och samhälle

   Författare :Karl Ericsson; [2023]
   Nyckelord :Multivariate statistical process control; Batch processes; Quality prediction;

   Sammanfattning : This Master's thesis focuses on improving the understanding and monitoring of the Hot Isostatic Pressing (HIP) sintering process used by Seco Tools AB to manufacture cemented carbides for cutting tools. While essential for producing cutting tools with superior hardness and toughness the HIP sintering process introduces a complex relationship between the selected process parameters and the achieved materials properties. LÄS MER

7. 5. 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