Sökning: "Time series clustering"

Visar resultat 1 - 5 av 32 avhandlingar innehållade orden Time series clustering.

1. 1. Data Stream Mining and Analysis : Clustering Evolving Data

   Författare :Christian Nordahl; Håkan Grahn; Veselka Boeva; Marie Netz; Plamen Angelov; Blekinge Tekniska Högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Data Stream Mining; Clustering; Data Streams; Data Mining; Computer Science; Datavetenskap;

   Sammanfattning : Streaming data is becoming more prevalent in our society every day. With the increasing use of technologies such as the Internet of Things (IoT) and 5G networks, the number of possible data sources steadily increases. Therefore, there is a need to develop algorithms that can handle the massive amount of data we now generate. LÄS MER

3. 2. Z-Series : Mining and learning from complex sequential data

   Författare :Zed Lee; Panagiotis Papapetrou; Tony Lindgren; Toon Calders; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; data- och systemvetenskap; Computer and Systems Sciences;

   Sammanfattning : The amount and complexity of sequential data collected across various domains have grown rapidly, posing significant challenges for extracting useful knowledge from such data sources. The complexity arises from diverse sequence representations with varying granularities, such as multivariate time series, histogram snapshots, and heterogeneous health records, which often describe a single data instance with multiple sequences. LÄS MER

4. 3. Data driven modeling in the presence of time series structure: : Improved bounds and effective algorithms

   Författare :Othmane Mazhar; Boualem Djehiche; Munther Dahleh; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Time series; Non-asymptotic estimation; Minimax; Change point detection; Hidden Markov model; State space model; Least square; Penalized Regression; Random covariance matrix; Concentration inequality; Chaining integral; Self-normalized martingale inequality; Cramér-Rao inequality; van Trees inequality; Matematisk statistik; Mathematical Statistics;

   Sammanfattning : This thesis consists of five appended papers devoted to modeling tasks where the desired models are learned from data sets with an underlying time series structure. We develop a statistical methodology for providing efficient estimators and analyzing their non-asymptotic behavior. LÄS MER

5. 4. Clustering Techniques for Mining and Analysis of Evolving Data

   Författare :Vishnu Manasa Devagiri; Veselka Boeva; Niklas Lavesson; Sindri Magnússon; Blekinge Tekniska Högskola; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Clustering analysis; Concept drift; Evolutionary clustering; Machine learning; Streaming data; Computer Science; Datavetenskap;

   Sammanfattning : The amount of data generated is on rise due to increased demand for fields like IoT, smart monitoring applications, etc. Data generated through such systems have many distinct characteristics like continuous data generation, evolutionary, multi-source nature, and heterogeneity. LÄS MER

7. 5. Some Contributions to Heteroscedastic Time Series Analysis and Computational Aspects of Bayesian VARs

   Författare :Oskar Gustafsson; Pär Stockhammar; Domenico Giannone; Stockholms universitet; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Time series; heteroscedasticity; variance stabilizing filters; Bayesian vector autoregressions; Bayesian optimization; variational inference; Statistics; statistik;

   Sammanfattning : Time-dependent volatility clustering (or heteroscedasticity) in macroeconomic and financial time series has been analyzed for more than half a century. The inefficiencies it causes in various inference procedures are well known and understood. Despite this, heteroscedasticity is surprisingly often neglected in practical work. LÄS MER