Sökning: "Nonlinear time series analysis"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden Nonlinear time series analysis.

  1. 1. Causal Discovery for Time Series : Based on Continuous Optimization

    Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Ali Nouri; [2023]
    Nyckelord :;

    Sammanfattning : Causal discovery is an important field of study that seeks to understand the underlying relationships between variables in a system. The goal of causal discovery is to discover the causal relationships from observational data and determine the direction of influence between variables. LÄS MER

  3. 2. Ocean rogue wave analysis for the development of safer navigation systems. : A Thesis submitted to the University of Gävle for the degree of Bachelor of Mathematics

    L3-uppsats, Högskolan i Gävle/Matematik

    Författare :Sergio Manzetti; [2023]
    Nyckelord :;

    Sammanfattning : Rogue waves are unexpectedly high waves of 2.5X the significant wave height and which occur in nearly all phases of nature, from  oceans, to fiber-optic cables and atmospheric air-masses. In the ocean, rogue waves pose a significant danger to shipping and fishing vessels and have been found to reach 27. LÄS MER

  4. 3. LSTM-based Directional Stock Price Forecasting for Intraday Quantitative Trading

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

    Författare :Isabella Mustén Ross; [2023]
    Nyckelord :Deep Learning; Long-Short-Term-Memory LSTM ; ARIMA; Financial Time Series Forecasting; Algorithmic Trading; Intraday Trading; Stock Prediction; Djupinlärning; LSTM; ARIMA; finansiella tidsserier; algoritmisk aktiehandel; intradagshandel; aktieprediktion;

    Sammanfattning : Deep learning techniques have exhibited remarkable capabilities in capturing nonlinear patterns and dependencies in time series data. Therefore, this study investigates the application of the Long-Short-Term-Memory (LSTM) algorithm for stock price prediction in intraday quantitative trading using Swedish stocks in the OMXS30 index from February 28, 2013, to March 1, 2023. LÄS MER

  5. 4. Autoregressiv analys på tidsseriedata från en kontorsbyggnad : Smarta byggnader i teori och praktik

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik

    Författare :Clara Grönlund; Astrid Gustafsson; [2020]
    Nyckelord :Smart buildings; ventilation; carbon dioxide levels; machine learning; modelling; PCA; AR; Smarta byggnader; ventilering; koldioxidhalter; maskininlärning; modellering; PCA; AR;

    Sammanfattning : The building sector is responsible for around 39% of the energy consumption in Sweden, and one way to work towards sustainable societies could be to make the buildings more energy efficient. One approach to make a building more energy efficient is to use knowledge gained from digitalization of the building and to make the building smart. LÄS MER

  7. 5. Developing a web-based system to visualize vegetation trends by a nonlinear regression algorithm

    Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskap

    Författare :Yufei Wei; [2016]
    Nyckelord :PolyTrend; nonlinear regression algorithm; vegetation trends; Physical Geography and Ecosystem Analysis; NDVI; Web Development; Django; MATLAB; Python; Earth and Environmental Sciences;

    Sammanfattning : Comparing with traditional linear regression methods that used to monitor vegetation trends, a nonlinear regression algorithm (PolyTrend) developed by Jamali et al. (2014) can provide more accurate information of vegetation trends by fitting a polynomial line with a degree of up to three for ASCII-formed time-series NDVI (Normalized Difference Vegetation Index) dataset of a single pixel. LÄS MER