Sökning: "klassificering av tidsserier"

Visar resultat 1 - 5 av 16 uppsatser innehållade orden klassificering av tidsserier.

  1. 1. Machine learning for detecting financial crime from transactional behaviour

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Signaler och system

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

    Sammanfattning : 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. LÄS MER

  3. 2. Time Series Analysis and Binary Classification in a Car-Sharing Service : Application of data-driven methods for analysing trends, seasonality, residuals and prediction of user demand

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

    Författare :Aksel Uhr; [2023]
    Nyckelord :Smart mobility; Car-sharing; Time series analysis; Demand prediction; Machine learning; Supervised learning; Binary classification; Random forest; Smart mobilitet; Bildelning; Tidsseriaanalys; Efterfrågansprediktering; Maskininlärning; Väglett lärande; Binär klassificering; Slumpmässiga skogar;

    Sammanfattning : Researchers have estimated a 20-percentage point increase in the world’s population residing in urban areas between 2011 and 2050. The increase in denser cities results in opportunities and challenges. Two of the challenges concern sustainability and mobility. LÄS MER

  4. 3. Forecasting Efficiency in Cryptocurrency Markets : A machine learning case study

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

    Författare :Erik Persson; [2022]
    Nyckelord :Cryptocurrencies; Financial time-series; Multi step-ahead forecasting; Machine Learning; Feature selection; Kryptovalutor; Finansiella tidsserier; Flerstegsprognoser; Maskininlärning; variabelselektion;

    Sammanfattning : Financial time-series are not uncommon to research in an academic context. This is possibly not only due to its challenging nature with high levels of noise and non-stationary data, but because of the endless possibilities of features and problem formulations it creates. LÄS MER

  5. 4. Classification of healthy and Parkinson’s disease state mice using whisker movements

    Kandidat-uppsats, KTH/Datavetenskap

    Författare :Philip Tumwa; Sandra Möttus; [2022]
    Nyckelord :;

    Sammanfattning : Modelling diseases in mice provides a useful way of studying the disease. The motor symptoms of Parkinson’s disease (PD) can be studied by observing the whisker movements of mice with PD condition. Mice use their whiskers to gather information about their environment and guide their locomotion. LÄS MER

  7. 5. Transfer learning techniques in time series analysis

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

    Författare :Robinson Sablons de Gélis; [2021]
    Nyckelord :Deep learning; Time series; Transfer learning; Self-supervised learning; Domain adaptation; Djupinlärning; tidsserier; överföringsinlärning; självövervakad inlärning; domänanpassning;

    Sammanfattning : Deep learning works best with vast andd well-distributed data collections. However, collecting and annotating large data sets can be very time-consuming and expensive. Moreover, deep learning is specific to domain knowledge, even with data and computation. E. LÄS MER