Sökning: "Feed Forward Neural Networks"

Visar resultat 1 - 5 av 27 uppsatser innehållade orden Feed Forward Neural Networks.

  1. 1. Evaluation of Artificial Neural Networks for Predictive Maintenance

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

    Författare :Anders Buhl; Hugo Hjertén; [2018]
    Nyckelord :Predictive Maintenance; Time Series Classification; Machine Learning; Artificial Neural Networks; FFNN; CNN; LSTM; Technology and Engineering;

    Sammanfattning : This thesis explores Artificial Neural Networks (ANNs) for predictive time series classification for Predictive Maintenance (PdM). Time slicing and time shifting are methods used, to enable the models to find features over time, and to predict into the future, respectively. LÄS MER

  2. 2. Recurrent neural networks in electricity load forecasting

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

    Författare :Samiul Alam; [2018]
    Nyckelord :Recurrent neural networks electricity load forecasting lstm renewable energy;

    Sammanfattning : In this thesis two main studies are conducted to compare the predictive capabilities of feed-forward neural networks (FFNN) and long short-term memory networks (LSTM) in electricity load forecasting. The first study compares univariate networks using past electricity load, as well as multivariate networks using past electricity load and air temperature, in day-ahead load forecasting using varying lookback periods and sparsity of past observations. LÄS MER

  3. 3. Recurrent neural networks for financial asset forecasting

    Master-uppsats, KTH/Matematisk statistik

    Författare :Gustaf Tegnér; [2018]
    Nyckelord :;

    Sammanfattning : The application of neural networks in finance has found renewed interest in the past few years. Neural networks have a proven capability of modeling non-linear relationships and have been proven widely successful in domains such as image and speech recognition. LÄS MER

  4. 4. Model comparison of patient volume prediction in digital health care

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

    Författare :Sasha Hellstenius; [2018]
    Nyckelord :Recurrent Neural Networks; LSTM; Patient Volume Prediction; Digital Healthcare;

    Sammanfattning : Accurate predictions of patient volume are an essential tool to improve resource allocation and doctor utilization in the traditional, as well as the digital health care domain. Varying methods for patient volume prediction within the traditional health care domain has been studied in contemporary research, while the concept remains underexplored within the digital health care domain. LÄS MER

  5. 5. Classification of Heart Sounds with Deep Learning

    Master-uppsats, Umeå universitet/Institutionen för datavetenskap

    Författare :Gustav Andersson; [2018]
    Nyckelord :;

    Sammanfattning : Health care is becoming more and more digitalized and examinations of patients from a distance are closer to reality than fiction. One of these examinations would be to automatically classify a patient-recorded audiosegment of its heartbeats as healthy or pathological. LÄS MER