Sökning: "Multivariate Time Series"

Visar resultat 1 - 5 av 105 uppsatser innehållade orden Multivariate Time Series.

1. 1. Spatio-temporal analysis of COVID-19 in Västra Götaland, Sweden

   Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

   Författare :Natalia Andreeva; [2023-08-23]
   Nyckelord :;

   Sammanfattning : Spatio-temporal analysis of COVID-19 data with the two different statistical approaches is the main objective of this thesis. The first classical approach, the Endemic-Epidemic framework (Held et al., 2005) is a class of multivariate time-series models for the incidence counts, obtained from the surveillance systems. LÄS MER

3. 2. 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

4. 3. Restaurant Daily Revenue Prediction : Utilizing Synthetic Time Series Data for Improved Model Performance

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för beräkningsvetenskap

   Författare :Stella Jarlöv; Anton Svensson Dahl; [2023]
   Nyckelord :demand forecasting; data augmentation; time series data; machine learning; restaurant industry; generative adversarial networks; TimeGAN; XGBoost;

   Sammanfattning : This study aims to enhance the accuracy of a demand forecasting model, XGBoost, by incorporating synthetic multivariate restaurant time series data during the training process. The research addresses the limited availability of training data by generating synthetic data using TimeGAN, a generative adversarial deep neural network tailored for time series data. LÄS MER

5. 4. 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

7. 5. Evaluating Brain-Inspired Machine Learning Models for Time Series Forecasting: A Comparative Study on Dynamical Memory in Reservoir Computing and Neural Networks

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Eddie Nevander Hellström; Johan Slettengren; [2023]
   Nyckelord :;

   Sammanfattning : Brain-inspired computing is a promising research field, with potential to encouragebreakthroughs within machine learning and enable us to solve complex problems in a moreefficient way. This study aims to compare the performance of brain-like machine learningalgorithms for time series forecasting. LÄS MER