Sökning: "Long Short-Term Memory Networks"

Visar resultat 16 - 20 av 175 uppsatser innehållade orden Long Short-Term Memory Networks.

  1. 16. Deep Learning in the Web Browser for Wind Speed Forecasting using TensorFlow.js

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

    Författare :Sara Moazez Gharebagh; [2023]
    Nyckelord :TensorFlow.js; JavaScript; Artificial Neural Networks; Deep Learning; Recurrent Neural Networks; Long Short-Term Memory; GatedRecurrent Units; TensorFlow.js; JavaScript; Artificiella Neurala Nätverk; Djupinlärning; Recurrent Neural Networks; Long Short-Term Memory; GatedRecurrent Units;

    Sammanfattning : Deep Learning is a powerful and rapidly advancing technology that has shown promising results within the field of weather forecasting. Implementing and using deep learning models can however be challenging due to their complexity. LÄS MER

  3. 17. Classifying personal data on contextual information

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

    Författare :Carl Dath; [2023]
    Nyckelord :Natural Language Processing; Machine Learning; Word2Vec; GloVe; BERT; Personal Data classification; Språkteknologi; Maskininlärning; Personlig Data Klassificering;

    Sammanfattning : In this thesis, a novel approach to classifying personal data is tested. Previous personal data classification models read the personal data before classifying it. However, this thesis instead investigates an approach to classify personal data by looking at contextual information frequently available in data sets. LÄS MER

  4. 18. Latency Prediction in 5G Networks by using Machine Learning

    Uppsats för yrkesexamina på avancerad nivå, Lunds universitet/Institutionen för reglerteknik

    Författare :Erica Elgcrona; Evrim Mete; [2023]
    Nyckelord :Technology and Engineering;

    Sammanfattning : This thesis presents a report of predicting latency in a 5G network by using deep learning techniques. The training set contained data of network parameters along with the actual latency, collected in a 5G lab environment during four different test scenarios. LÄS MER

  5. 19. Forecasting Codeword Errors in Networks with Machine Learning

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

    Författare :Angus Hansson Svan; [2023]
    Nyckelord :Forecasting; Codeword Errors; Hybrid Fiber-Coaxial; Long Short-Term Memory; Multilayer Perceptron; Hybridfiber-koaxialt nätverk; HFC; LSTM; MLP;

    Sammanfattning : With an increasing demand for rapid high-capacity internet, the telecommunication industry is constantly driven to explore and develop new technologies to ensure stable and reliable networks. To provide a competitive internet service in this growing market, proactive detection and prevention of disturbances are key elements for an operator. LÄS MER

  7. 20. Supervised Algorithm for Predictive Maintenance

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

    Författare :Haida Lu; [2023]
    Nyckelord :Long short-term memory; Predictive maintenance; Remaining useful life; Embedded Artificial Intelligence; Långt korttidsminne; förebyggande underhåll; återstående livslängd; inbyggd artificiell intelligens;

    Sammanfattning : Predictive maintenance plays a crucial role in preventing unexpected equipment failures and maintaining assets in good operating conditions in various systems. One such scenario where predictive maintenance has been widely used is in battery management systems for electronic vehicles based on lithium batteries, where the risk of failure can be reduced by predicting the remaining useful life of the lithium battery. LÄS MER