Essays about: "multivariate time series data"

Showing result 16 - 20 of 89 essays containing the words multivariate time series data.

  1. 16. Evaluating the use of Brush and Tooltip for Time Series visualizations: A comparative study

    University essay from Malmö universitet/Fakulteten för teknik och samhälle (TS)

    Author : Sebastian Helin; André Eklund; [2023]
    Keywords : Graphical Perception Tooltip Brush Accuracy Estimation Time Univariate Multivariate Time Series Visualization;

    Abstract : This study uses a combination of user testing and analysis to evaluate the impact of brush and tooltip on the comprehension of time series visualizations. Employing a sequential mixed-methods approach, with qualitative data from semi-structured interviews used to inform the design of a visualization tool, followed by a quantitative user study to validate it. READ MORE

  3. 17. Machine learning for detecting financial crime from transactional behaviour

    University essay from Uppsala universitet/Signaler och system

    Author : Markus Englund; [2023]
    Keywords : machine learning; deep learning; financial crime; time series; time series classification; XGBoost; maskininlärning; djupinlärning; finansiell brottslighet; tidsserier; klassificering av tidsserier; XGBoost;

    Abstract : Banks and other financial institutions are to a certain extent obligated to ensure that their services are not utilized for any type of financial crime. This thesis investigates the possibility of analyzing bank customers' transactional behaviour with machine learning to detect if they are involved in financial crime. READ MORE

  4. 18. Anomaly detection for prediction of failures in manufacturing environments : Machine learning based semi-supervised anomaly detection for multivariate time series to predict failures in a CNC-machine

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

    Author : Felix Boltshauser; [2023]
    Keywords : Machine learning; Anomaly Detection; DeepAnT; ROCKET; OCSVM; manufacturing; predictive maintenance; Maskin inlärning; Anomali Detektion; DeepAnT; ROCKET; OCSVM; tillverkning; prediktivt underhåll;

    Abstract : For manufacturing enterprises, the potential of collecting large amounts of data from production processes has enabled the usage of machine learning for prediction-based monitoring and maintenance of machines. Yet common maintenance strategies still include reactive handling of machine failures or schedule-based maintenance conducted by experienced personnel. READ MORE

  5. 19. Sign of the Times : Unmasking Deep Learning for Time Series Anomaly Detection

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

    Author : Daniel Richards Ravi Arputharaj; [2023]
    Keywords : Anomaly detection; multivariate time series data; deep learning models; model complexity; resource-constrained systems; Variational Autoencoders VAEs ; Convolutional Variational Autoencoders; evaluation metrics in time series; Anomalidetektering; Multivariata tidsseriedata; Djupinlärningsmodeller; Modellkomplexitet; Resursbegränsade system; Variational Autoencoders VAEs ; Konvolutionella Variational Autoencoders; Utvärderingsmått inom tidsserier;

    Abstract : Time series anomaly detection has been a longstanding area of research with applications across various domains. In recent years, there has been a surge of interest in applying deep learning models to this problem domain. READ MORE

  6. 20. Unsupervised Anomaly Detection in Multivariate Time Series Using Variational Autoencoders

    University essay from Lunds universitet/Matematik LTH

    Author : Elias Aronsson; [2023]
    Keywords : Anomaly Detection; Variational Autoencoder VAE ; Unsupervised Learning; Machine learning; AI; Technology and Engineering;

    Abstract : In this master’s thesis, a novel unsupervised anomaly detection tool was developed in collaboration with Sandvik Rock Processing to assist engineers and experts in analyzing large amounts of sensor data from cone crushers used in the stone crushing industry. The tool focuses on analyzing power, pressure, and CSS sensor data. READ MORE