Sökning: "Tidsserie data"
Visar resultat 1 - 5 av 84 uppsatser innehållade orden Tidsserie data.
1. Robust Statistical Jump Models with Feature Selection
Master-uppsats, Lunds universitet/Matematisk statistikSammanfattning : 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
2. Extraction of Global Features for enhancing Machine Learning Performance
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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
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 fordonsdesignSammanfattning : 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
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)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
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)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