Sökning: "recurrent artificial neural networks"

Visar resultat 1 - 5 av 57 uppsatser innehållade orden recurrent artificial neural networks.

  1. 1. Time Series Forecasting on Database Storage

    Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Författare :Pranav Patel; [2024]
    Nyckelord :Machine Learning; Time Series Forecasting; Prediction; Neural Networks; CNN; RNN; Database Storage;

    Sammanfattning : Time Series Forecasting has become vital in various industries ranging from weather forecasting to business forecasting. There is a need to research database storage solutions for companies in order to optimize resource allocation, enhance decision making process and enable predictive data storage maintenance. LÄS MER

  3. 2. Artificial Neural Networks for Financial Time Series Prediction

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Dana Malas; [2023]
    Nyckelord :artificial neural networks; time series analysis; deep learning; finance; long short-term memory; simple moving average;

    Sammanfattning : Financial market forecasting is a challenging and complex task due to the sensitivity of the market to various factors such as political, economic, and social factors. However, recent advances in machine learning and computation technology have led to an increased interest in using deep learning for forecasting financial data. LÄS MER

  4. 3. Neural Network-Based Residential Water End-Use Disaggregation

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

    Författare :Cajsa Pierrou; [2023]
    Nyckelord :Residential water end-use; Flow disaggregation; Time series classification; Artificial neural network; Smart water meter; Slutanvändning av vatten i hushåll; Flödesdisaggregering; Tidsserieklassificering; Artificiella neurala nätverk; Smart vattenmätare;

    Sammanfattning : Sustainable management of finite resources is vital for ensuring livable conditions for both current and future generations. Measuring the total water consumption of residential households at high temporal resolutions and automatically disaggregating the sole signal into classified end usages (e.g. LÄS MER

  5. 4. 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

  7. 5. Trigger-Level Multiple Electron Event Classification with LDMX using Artificial Neural Networks

    Master-uppsats, Lunds universitet/Partikel- och kärnfysik; Lunds universitet/Fysiska institutionen

    Författare :Jacob Lindahl; [2023]
    Nyckelord :LDMX; ANN; CNN; GNN; RNN; DM; Physics and Astronomy;

    Sammanfattning : Artificial neural networks is a powerful tool for classifying and identifying patterns in large amounts of data. One of the possible tasks of these networks is classification of data into categories. LÄS MER