Sökning: "temporal networks"
Visar resultat 1 - 5 av 165 uppsatser innehållade orden temporal networks.
1. A space-time shape for easier spatiotemporal visualization in traffic networks
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknikSammanfattning : Modern big data systems are enabling new possibilities that never were thought possible in the past. The ability to gather massive data on an individual level has made fields like space-time geography bloom in the latest decennia. The usage of shapes in a 3D space allows us to visualize certain phenomena over time. LÄS MER
2. Time Series Forecasting on Database Storage
Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Sammanfattning : Time Series Forecasting has become vital in various industries ranging from weather forecasting to business forecasting. There is a need to research database storage solutions for companies in order to optimize resource allocation, enhance decision making process and enable predictive data storage maintenance. LÄS MER
3. Drivers of sea level variability using neural networks
Master-uppsats, Göteborgs universitet/Institutionen för geovetenskaperSammanfattning : Understanding the forcing of regional sea level variability is crucial as many people all over the world live along the coasts and are endangered by extreme sea levels and the global sea level rise. The adding of fresh water into the oceans due to melting of the Earth’s land ice together with thermosteric changes has led to a rise of the global mean sea level with an accelerating rate during the twentieth century. LÄS MER
4. Neural Network-based Anomaly Detection Models and Interpretability Methods for Multivariate Time Series Data
Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskapSammanfattning : 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
5. Restaurant Daily Revenue Prediction : Utilizing Synthetic Time Series Data for Improved Model Performance
Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för beräkningsvetenskapSammanfattning : 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