Sökning: "sekventiella"

Visar resultat 16 - 20 av 102 uppsatser innehållade ordet sekventiella.

  1. 16. Hybrid Deep Learning Model for Cellular Network Traffic Prediction : Case Study using Telecom Time Series Data, Satellite Imagery, and Weather Data

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

    Författare :Ali Shibli; [2022]
    Nyckelord :Cellular network traffic; multi-modal; satellite imagery; weather data; LSTM; CNN; time series; Trafic sur les réseaux cellulaires; multimodal; imagerie satellite; données météo; LSTM; CNN; séries temporelles; Förutsägelse av mobilnätstrafik; multimodal modell; satellitbilder; väderdata; LSTM; CNN; tidsseriein;

    Sammanfattning : Cellular network traffic prediction is a critical challenge for communication providers, which is important for use cases such as traffic steering and base station resources management. Traditional prediction methods mostly rely on historical time-series data to predict traffic load, which often fail to model the real world and capture surrounding environment conditions. LÄS MER

  3. 17. Geospatial Trip Data Generation Using Deep Neural Networks

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

    Författare :Aditya Deepak Udapudi; [2022]
    Nyckelord :Deep Learning; Geospatial; Generative Adversarial Network GAN ; Deep Learning; Geospatial; Generativa Motståndsnätverk GAN ;

    Sammanfattning : Development of deep learning methods is dependent majorly on availability of large amounts of high quality data. To tackle the problem of data scarcity one of the workarounds is to generate synthetic data using deep learning methods. LÄS MER

  4. 18. Data-driven Discovery of Real-time Road Compaction Parameters

    Master-uppsats, KTH/Matematisk statistik

    Författare :Yuqi Shao; [2022]
    Nyckelord :statistics; machine learning; road compaction; statistik; maskininlärning; vägpackning;

    Sammanfattning : Road compaction is the last and important stage in road construction. Both under-compaction and over-compaction are inappropriate and may lead to road failures. Intelligent compactors has enabled data gathering and edge computing functionalities, which introduces possibilities in data-driven compaction control. LÄS MER

  5. 19. Basil-GAN

    Master-uppsats, KTH/Matematisk statistik

    Författare :Jonatan Risberg; [2022]
    Nyckelord :GAN; mathematical statistics; deep neural networks; generative models; latent space exploration; sequential data; GAN; matematisk statistik; djupa neurala nätverk; generativa modeller; utforskning av latenta rum; sekventiell data;

    Sammanfattning : Developments in computer vision has sought to design deep neural networks which trained on a large set of images are able to generate high quality artificial images which share semantic qualities with the original image set. A pivotal shift was made with the introduction of the generative adversarial network (GAN) by Goodfellow et al.. LÄS MER

  7. 20. Controlling Autonomous Baker Robot Using Signal Temporal Logic and Control Barrier Functions

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

    Författare :Gustav Bernpaintner; Marcus Allen; [2022]
    Nyckelord :autonomous systems; signal temporal logic; control barrier function; quadratic programming;

    Sammanfattning : Autonomous systems are slowly moving into the mainstream with things like self driving cars and autonomous robots in storage facilities already in use today. The aim of this project is to simulate a virtual bakery with a baker-robot (agent)that is able to complete recipes within strict deadlines. LÄS MER