Sökning: "Prediction-error method"

Visar resultat 1 - 5 av 36 uppsatser innehållade orden Prediction-error method.

  1. 1. A Machine Learning Approach on Analysis of Emission Spectra for Application in XFEL Experiments

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för fysik och astronomi

    Författare :Harald Agelii; [2023]
    Nyckelord :Structural biology; Machine learning; Neural networks; emission spectrum; XFEL; X-ray free electron laser; SFX; Serial femtosecond X-ray crystallography; Proteins; Diagnostics;

    Sammanfattning : In this thesis we investigate two potential applications of machine learning in the context of X-ray imaging and spectroscopy of biological samples, particularly such using X-ray free electron lasers (XFEL). We first investigate the possibility of using an emission spectrum, recorded from a sample after being probed by an incident X-ray, as a diagnostic tool. LÄS MER

  3. 2. Wind Turbine Recovery Forecasting using Survival Analysis

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Anton Palets; [2023]
    Nyckelord :Survival analysis; Recovery Forecast; Wind Turbine; Availability Forecast; AFT model; Aalen s model; Cox regression; Cox Proportional Hazards; Variation Processes; Mathematics and Statistics;

    Sammanfattning : The goal of this thesis is to present a methodology for predicting time until recovery of failed wind turbines. The necessity is motivated by the potential for more accurate wind energy export forecasts. The current approach rests entirely on having an expert examine the turbine and produce a time estimate. LÄS MER

  4. 3. System Identification of a Fixed-Wing UAV Using a Prediction Error Method

    Master-uppsats, Linköpings universitet/Reglerteknik

    Författare :Trulsa Eriksson; [2023]
    Nyckelord :System identification; Fixed-wing UAV; Modelling; Parameter estimation;

    Sammanfattning : Unmanned aerial vehicles (UAVs) is a rapidly expanding area of research due to their versatile usage, such as inspection of places inaccessible to humans and surveillance missions. This creates a demand for a reliable model that can accurately describe the dynamics of the system in order to improve the performance of the vehicle. LÄS MER

  5. 4. Machine Learning Based Stock Price Prediction by Integrating ARIMA model and Sentiment Analysis with Insights from News and Information

    Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Teja Sai Vaibhav Boppana; Joseph Sudheer Vinakonda; [2023]
    Nyckelord :Machine Learning; Market Trends; News; Headlines Stock Price Prediction; VADER.;

    Sammanfattning : Background: Predicting stock prices in today’s complex financial landscape is asignificant challenge. An innovative approach to address this challenge is integrating sentiment analysis techniques with the well-established Autoregressive IntegratedMoving Average (ARIMA) model. LÄS MER

  7. 5. Automatic Detection of Common Signal Quality Issues in MRI Data using Deep Neural Networks

    Master-uppsats, Linköpings universitet/Institutionen för medicinsk teknik

    Författare :Erika Ax; Elin Djerf; [2023]
    Nyckelord :mr; magnetic resonance; machine learning; deep learning; anomaly detection; U-Net; autoencoder; 3D; classification; reconstruction; artefacts;

    Sammanfattning : Magnetic resonance imaging (MRI) is a commonly used non-invasive imaging technique that provides high resolution images of soft tissue. One problem with MRI is that it is sensitive to signal quality issues. The issues can arise for various reasons, for example by metal located either inside or outside of the body. LÄS MER