Sökning: "LSTM model"

Visar resultat 1 - 5 av 341 uppsatser innehållade orden LSTM model.

  1. 1. Predicting Electricity Consumption with ARIMA and Recurrent Neural Networks

    Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Klara Enerud; [2024]
    Nyckelord :time series forecasting; ARIMA; recurrent neural networks; LSTM; electricity forecasting; EED forecasting;

    Sammanfattning : Due to the growing share of renewable energy in countries' power systems, the need for precise forecasting of electricity consumption will increase. This paper considers two different approaches to time series forecasting, autoregressive moving average (ARMA) models and recurrent neural networks (RNNs). LÄS MER

  3. 2. Predicting Navigational Patterns in Web Applications using Machine Learning Techniques

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

    Författare :Patric Balan; Gustav Jönemo; [2024]
    Nyckelord :Technology and Engineering;

    Sammanfattning : In large corporations, customer support is a costly service, and an area of constant optimization. Solutions to increase efficiency and decrease bottlenecks are constantly needed. LÄS MER

  4. 3. 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

  5. 4. CNN-LSTM architecture for predicting hazardous driving situations

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

    Författare :Noomi Lindblad; Stefani Platakidou; [2023-10-05]
    Nyckelord :Data science; Machine learning; LSTM; CNN; Vehicle data; Hazardous driving situation; Deep learning;

    Sammanfattning : This study aims to investigate how a CNN-LSTM model can be used together with recorded vehicle data from trucks and external weather data in order to predict a hazardous driving situation. The dataset consists of three-second-long driving snippets from customer and development trucks registered within Europe. LÄS MER

  7. 5. Drivers of sea level variability using neural networks

    Master-uppsats, Göteborgs universitet/Institutionen för geovetenskaper

    Författare :Linn Carlstedt; [2023-05-10]
    Nyckelord :;

    Sammanfattning : Understanding the forcing of regional sea level variability is crucial as many people all over the world live along the coasts and are endangered by extreme sea levels and the global sea level rise. The adding of fresh water into the oceans due to melting of the Earth’s land ice together with thermosteric changes has led to a rise of the global mean sea level with an accelerating rate during the twentieth century. LÄS MER