Sökning: "long short-term memory"

Visar resultat 1 - 5 av 224 uppsatser innehållade orden long short-term memory.

  1. 1. Driver Behavior Classification in Electric Vehicles

    Master-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

    Författare :FEDERICA COMUNI; CHRISTOPHER MÉSZÁROS; [2021-07-06]
    Nyckelord :Aggressive driver behavior; Driver behavior classification; Self-attention; Recurrence plots; active learning; Active deep dropout; Gradual pseudo labeling;

    Sammanfattning : Studies have shown that driving style affects the energy consumption of electric vehicles, with aggressive driving consuming up to 30% more energy than moderate driving. Therefore, modeling of aggressive driving can provide a more precise estimation of the energy consumption and the remaining range of a vehicle. LÄS MER

  2. 2. Sequential Anomaly Detection for Log Data Using Deep Learning

    Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

    Författare :Lina Hammargren; Wei Wu; [2021-06-14]
    Nyckelord :anomaly detection; recurrent neural network; long short-term memory; semi-supervised learning; seq2seq; transformer; unsupervised learning; log analysis;

    Sammanfattning : AbstractSoftware development with continuous integration changes needs frequent testing forassessment. Analyzing the test output manually is time-consuming and automatingthis process could be beneficial to an organization. LÄS MER

  3. 3. Deep Learning for Driver Sleepiness Classification using Bioelectrical Signals and Karolinska Sleepiness Scale

    Master-uppsats, Linköpings universitet/Institutionen för medicinsk teknik

    Författare :Maja Jonsson; Jennifer Brown; [2021]
    Nyckelord :Sleepiness detection; EEG; KSS; deep learning; driving; classification;

    Sammanfattning : Driver sleepiness contributes to a large amount of all road traffic crashes. Developing an objective measurement of driver sleepiness in order to prevent eventual traffic accidents is desirable. LÄS MER

  4. 4. Training Autoencoders for feature extraction of EEG signals for motor imagery

    Kandidat-uppsats, Mälardalens högskola/Akademin för innovation, design och teknik

    Författare :Casper Wahl; [2021]
    Nyckelord :;

    Sammanfattning : Electroencephalography (EEG) is a common technique used to read brain activity from an individual, and can be used for a wide range of applications, one example is during the rehab process of stroke victims. Loss of motor function is a common side effect of strokes, and the EEG signals can show if sufficient activation of the part of the brain related to the motor function that the patient is training has been achieved. LÄS MER

  5. 5. Sentiment towards the COVID-19 pandemic - A valuable instrument for predicting prices in the US stock market?

    D-uppsats, Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

    Författare :Rebecca Sehlbach; Yuhan Hu; [2021]
    Nyckelord :COVID-19 pandemic; sentiment analysis; Twitter; LSTM model; stock market prediction;

    Sammanfattning : This thesis investigates the impact of sentiment towards the COVID-19 pandemic on stock prices by incorporating sentiment into the existing Long Short-Term Memory (LSTM) model for predicting stock prices in the United States. Existing research on this field has principally been conducted before the outbreak of the pandemic, while more current studies have largely focused on overall sentiment rather than sentiment towards the pandemic. LÄS MER