Sökning: "Tidsserie data"

Visar resultat 1 - 5 av 84 uppsatser innehållade orden Tidsserie data.

  1. 1. Robust Statistical Jump Models with Feature Selection

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Jonatan Persson; [2023]
    Nyckelord :Clustering; Jump; Feature selection; Robust; Mathematics and Statistics;

    Sammanfattning : A large area in statistics and machine learning is cluster analysis. This field of research concerns the design of algorithms that allow computers to automatically categorize a set of observations into different groups in a reasonable way, without any prior information about which observations belongs to which group. LÄS MER

  3. 2. Extraction of Global Features for enhancing Machine Learning Performance

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

    Författare :Abyel Tesfay; [2023]
    Nyckelord :Machine Learning; Deep Learning; Feature Extraction; Global Features; Time-series data; Bioprocessing; Maskininlärning; Djupinlärning; Funktionsextraktion; Globala Funktioner; Tidsserie data; Biobearbetning;

    Sammanfattning : Data Science plays an essential role in many organizations and industries to become data-driven in their decision-making and workflow, as models can provide relevant input in areas such as social media, the stock market, and manufacturing industries. To train models of quality, data preparation methods such as feature extraction are used to extract relevant features. LÄS MER

  4. 3. Shock absorber dynamics : A parameter study of damper physical quantitiesand their effect on automobile comfort and control

    Master-uppsats, KTH/Väg- och spårfordon samt konceptuell fordonsdesign

    Författare :David Stridfeldt; Jonsson Gustav; [2023]
    Nyckelord :Shock absorbers; dampers; parameter study; valve dynamics; comfort; control; Stötdämpare; dämpare; parameterstudie; ventildynamik; komfort; kontroll;

    Sammanfattning :   Damper performance is most commonly characterized by the damper’s forcevelocity behaviour. Different damper layouts and valving methods for creating oil flow constrictions bring different physical properties, outside of this conventional measure. LÄS MER

  5. 4. Football Trajectory Modeling Using Masked Autoencoders : Using Masked Autoencoder for Anomaly Detection and Correction for Football Trajectories

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

    Författare :Sandra Tor; [2023]
    Nyckelord :Machine Learning; Autoencoders; Masked autoencoders; Time series; Trajectory modeling; Time series modeling; Anomaly detection; Anomaly correction; Football; Maskininlärning; Autoencoders; Maskerade autoencoders; Tidsserie; Banmodellering; Tidsseriemodellering; Avvikelsedetektering; Avvikelsekorrigering; Fotboll;

    Sammanfattning : Football trajectory modeling is a powerful tool for predicting and evaluating the movement of a football and its dynamics. Masked autoencoders are scalable self-supervised learners used for representation learning of partially observable data. LÄS MER

  7. 5. An empirical study of the impact of data dimensionality on the performance of change point detection algorithms

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

    Författare :Léo Noharet; [2023]
    Nyckelord :Time series segmentation; Change point detection; Multivariate time series; Data dimensionality; Tidsserie-segmentering; Förändringspunkts detektering; Mulitvariabla tidsserier; Data dimentionalitet;

    Sammanfattning : When a system is monitored over time, changes can be discovered in the time series of monitored variables. Change Point Detection (CPD) aims at finding the time point where a change occurs in the monitored system. LÄS MER