Sökning: "Long Short-Term Memory Networks"

Visar resultat 6 - 10 av 175 uppsatser innehållade orden Long Short-Term Memory Networks.

  1. 6. Modelling Proxy Credit Cruves Using Recurrent Neural Networks

    Master-uppsats, KTH/Matematisk statistik

    Författare :Lucas Fageräng; Hugo Thoursie; [2023]
    Nyckelord :Deep Neural Networks; Credit Risk; Financial Modelling; LSTM; Credit Default Swaps; Credit Valuation Adjustment; Djupa Neurala Nätverk; Kreditrisk; Finansiell Modellering; LSTM; Kreditswappar; Kreditvärderingsjustering;

    Sammanfattning : Since the global financial crisis of 2008, regulatory bodies worldwide have implementedincreasingly stringent requirements for measuring and pricing default risk in financialderivatives. Counterparty Credit Risk (CCR) serves as the measure for default risk infinancial derivatives, and Credit Valuation Adjustment (CVA) is the pricing method used toincorporate this default risk into derivatives prices. LÄS MER

  2. 7. 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

  3. 8. Unauthorised Session Detection with RNN-LSTM Models and Topological Data Analysis

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Nazar Maksymchuk Netterström; [2023]
    Nyckelord :Recurrent Neural Network; Long-Short-Term-Memory; Topological Data Analysis; Session based data; Anomaly detection; Time-series analysis; Imbalanced data; Master thesis; Neurala nätverk; Topologisk data analys; Detektion av avvikelse; Sessionsbaserad data; Tidserieanalys; Inbalancerad data; Masteruppsats;

    Sammanfattning : This thesis explores the possibility of using session-based customers data from Svenska Handelsbanken AB to detect fraudulent sessions. Tools within Topological Data Analysis are employed to analyse customers behavior and examine topological properties such as homology and stable rank at the individual level. LÄS MER

  4. 9. 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

  5. 10. Assessing Electricity Prices and Their Driving Mechanisms in Brazil with Neural Networks

    Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)

    Författare :Henrique Costabile; [2023]
    Nyckelord :;

    Sammanfattning : In general, electricity prices are very volatile and derive from many external variables. In Brazil, this price is determined by computer models developed and operated by government organizations. The supply and demand relationships are not enough to determine prices in Brazilian submarkets. LÄS MER