Essays about: "Autoregressive Integrated Moving Average"

Showing result 1 - 5 of 42 essays containing the words Autoregressive Integrated Moving Average.

  1. 1. Evaluating Brain-Inspired Machine Learning Models for Time Series Forecasting: A Comparative Study on Dynamical Memory in Reservoir Computing and Neural Networks

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Eddie Nevander Hellström; Johan Slettengren; [2023]
    Keywords : ;

    Abstract : Brain-inspired computing is a promising research field, with potential to encouragebreakthroughs within machine learning and enable us to solve complex problems in a moreefficient way. This study aims to compare the performance of brain-like machine learningalgorithms for time series forecasting. READ MORE

  3. 2. On modelling OMXS30 stocks - comparison between ARMA models and neural networks

    University essay from Uppsala universitet/Matematiska institutionen

    Author : Irina Zarankina; [2023]
    Keywords : ARMA; ARIMA; LSTM; time series; statistics;

    Abstract : This thesis compares the results of the performance of the statistical Autoregressive integrated moving average (ARIMA) model and the neural network Long short-term model (LSTM) on a data set, which represents a market index. Both models are used to predict monthly, daily, and minute close prices of the OMX Stockholm 30 Index. READ MORE

  4. 3. Portfolio Risk Modelling in Venture Debt

    University essay from KTH/Matematisk statistik

    Author : John Eriksson; Jacob Holmberg; [2023]
    Keywords : Startup Default Probability; Venture Debt; Gaussian Copula; Value-at-Risk; Expected Shortfall; Exposure at Default; Loss Given Default; Forecast; Linear Dynamic System; ARIMA Time Series; Monte Carlo Simulation; Linear Regression; Central Limit Theorem;

    Abstract : This thesis project is an experimental study on how to approach quantitative portfolio credit risk modelling in Venture Debt portfolios. Facing a lack of applicable default data from ArK and publicly available sets, as well as seeking to capture companies that fail to service debt obligations before defaulting per se, we present an approach to risk modeling based on trends in revenue. READ MORE

  5. 4. Predicting Waveforms with Machine Learning for Efficient Triggering in Monitoring Systems

    University essay from Mälardalens universitet/Akademin för innovation, design och teknik

    Author : Amanda Rautio; [2023]
    Keywords : ;

    Abstract : Energy systems need to evolve to meet the requirements of the modern world and the future. Hence, substantial effort is needed at an academic and industrial level to develop valuable diagnostic techniques. READ MORE

  6. 5. Passenger flow prediction : Finding and developing a sustainable machine learning model for airport passenger flow prediction

    University essay from Uppsala universitet/Matematiska institutionen

    Author : Tomas Haglund; Oskar Jonsson; [2023]
    Keywords : Maskininlärning flyplats flyg flygindustrin passanger flow AI;

    Abstract : There are many outdated routines and processes in today's aviation industry that major airlines lack the motivation to update. While this may not hold any direct security concerns, it creates bottlenecks at checks and high salary costs for otiose airport personnel. READ MORE