Essays about: "multivariate techniques"

Showing result 1 - 5 of 45 essays containing the words multivariate techniques.

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

   University essay from Stockholms universitet/Institutionen för data- och systemvetenskap

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

   Abstract : 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. READ MORE

3. 2. Forecasting Swedish FCR-D Prices using Penalized Multivariate Time Series Techniques

   University essay from Lunds universitet/Nationalekonomiska institutionen; Lunds universitet/Statistiska institutionen

   Author : Franz Lennart Wunderlich; Sebastian Brugger; [2023]
   Keywords : Swedish Energy Market; Multivariate Time-Series; Lasso; Forecasting; Noise Filtering; Business and Economics;

   Abstract : The Swedish energy market is becoming more and more sustainable, with an increasing volume and number of diversified energy sources being continuously added to the mix. To stabilize the grid frequency, auctions are held to offer energy providers incentives to produce or consume energy on short notice. READ MORE

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

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

   Abstract : 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. READ MORE

5. 4. Finding Causal Relationships Among Metrics In A Cloud-Native Environment

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Suresh Rishi Nandan; [2023]
   Keywords : Causality; Causal Discovery; Bayesian Network; Conditional Independence; Partial Correlation; Ensemble Causal Discovery; Anomaly Detection; Causal Graphs; Causality; Causal Discovery; Bayesian Network; Conditional Indeberoende; partiell korrelation; Ensemble Causal Discovery; Anomali Detektion; kausala grafer;

   Abstract : 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. READ MORE

6. 5. Evaluating clustering techniques in financial time series

   University essay from Uppsala universitet/Avdelningen för systemteknik

   Author : Johan Millberg; [2023]
   Keywords : clustering; machine learning; financial time series; time series; unsupervised learning; cluster validation; cluster evaluation; klustring; klusteranalys; finansiella tidsserier; maskininlärning; klustervalidering; evalueringsteknik;

   Abstract : This degree project aims to investigate different evaluation strategies for clustering methodsused to cluster multivariate financial time series. Clustering is a type of data mining techniquewith the purpose of partitioning a data set based on similarity to data points in the same cluster,and dissimilarity to data points in other clusters. READ MORE