Sökning: "gru"

Visar resultat 1 - 5 av 67 uppsatser innehållade ordet gru.

  1. 1. Predicting Cryptocurrency Prices with Machine Learning Algorithms: A Comparative Analysis

    Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Harsha Nanda Gudavalli; Khetan Venkata Ratnam Kancherla; [2023]
    Nyckelord :Bitcoin; Cryptocurrency; Machine Learning;

    Sammanfattning : Background: Due to its decentralized nature and opportunity for substantial gains, cryptocurrency has become a popular investment opportunity. However, the highly unpredictable and volatile nature of the cryptocurrency market poses a challenge for investors looking to predict price movements and make profitable investments. LÄS MER

  3. 2. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

    Master-uppsats, KTH/Mekatronik och inbyggda styrsystem

    Författare :Helgi Hrafn Björnsson; Jón Kaldal; [2023]
    Nyckelord :Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

    Sammanfattning : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. LÄS MER

  4. 3. A Deep Learning Approach To Vehicle Fault Detection Based On Vehicle Behavior

    Master-uppsats, Malmö universitet/Institutionen för datavetenskap och medieteknik (DVMT)

    Författare :Rafi Khaliqi; Cozma Iulian; [2023]
    Nyckelord :Deep learning; attention mechanism; vehicle fault detection; CNN; Bi-LSTM; Bi-GRU; Supervised classification;

    Sammanfattning : Vehicles and machinery play a crucial role in our daily lives, contributing to our transportationneeds and supporting various industries. As society strives for sustainability, the advancementof technology and efficient resource allocation become paramount. LÄS MER

  5. 4. Data Driven Model Identification for Remote Electrical Tilt Systems

    Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Raphaël Ashruf; [2023]
    Nyckelord :;

    Sammanfattning : This thesis explores the use of supervised machine learning for modelling the dynamics of Remote Electrical Tilt (RET) telecom systems. Three methodologies, including linear regressionfor linear dynamics models, Gaussian Process (GP) regression, and Recurrent Neural Networks (RNN) with Gated Recurrent Units (GRU) are proposed. LÄS MER

  7. 5. Temporal Localization of Representations in Recurrent Neural Networks

    Master-uppsats, Högskolan Dalarna/Institutionen för information och teknik

    Författare :Asadullah Najam; [2023]
    Nyckelord :Recurrent Neural Networks RNNs ; Deep Learning; Time Series Prediction; Exploding Values; Gradient Decay; Long Short-Term Memory LSTMs ; Gated Recurrent Units GRUs ; Attention Mechanism; Moving Representations; Localizing Representations;

    Sammanfattning : Recurrent Neural Networks (RNNs) are pivotal in deep learning for time series prediction, but they suffer from 'exploding values' and 'gradient decay,' particularly when learning temporally distant interactions. Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) have addressed these issues to an extent, but the precise mitigating mechanisms remain unclear. LÄS MER