Essays about: "spatio-temporal pattern detection"

Found 3 essays containing the words spatio-temporal pattern detection.

  1. 1. Segmenting cruise passengers based on their spatio-temporal similarity : an approach utilising dynamic time warping

    University essay from Uppsala universitet/Kulturgeografiska institutionen

    Author : Pauline Borg; [2023]
    Keywords : cruise tourism; dynamic time warping; cluster analysis; overcrowding; tourist mobility; kryssningsturism; dynamic time warping; klusteranalys; trängsel; turistmobilitet;

    Abstract : The present thesis utilises dynamic time warping and cluster analysis with the aim of discovering different touristic profiles. GPS data of cruise passengers intra-destination movement at the destination of Visby, Gotland, was used in the analysis. READ MORE

  3. 2. Adding temporal plasticity to a self-organizing incremental neural network using temporal activity diffusion

    University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)

    Author : Emil Lundberg; [2015]
    Keywords : ANN; artificial neural network; SOINN; SOTPAR; SOTPAR2; prediction; spatio-temporal pattern detection; temporal activity diffusion; pattern recognition; unsupervised learning; vector quantization; ANN; artificiellt neuralt nätverk; artificiella neurala nätverk; SOINN; SOTPAR; SOTPAR2; förutsägelse; spatio-temporal mönsterdetekion; temporal aktivitetsdiffusion; mönsterigenkänning; oövervakad inlärning; vektorkvantisering;

    Abstract : Vector Quantization (VQ) is a classic optimization problem and a simple approach to pattern recognition. Applications include lossy data compression, clustering and speech and speaker recognition. READ MORE

  4. 3. Spatio-temporal outlier detection in streaming trajectory data

    University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)

    Author : MÁTÉ SZEKÉR; [2014]
    Keywords : ;

    Abstract : This thesis investigates the problem of detecting spatiotemporalanomalies in streamed trajectory data using both supervised and unsupervised algorithms. Anomaly detection can be understood as an unsupervised classification problem which requires the knowledge of the normal course of events or how the anomalies manifest themselves. READ MORE