Essays about: "autoregressive behavior"
Showing result 1 - 5 of 11 essays containing the words autoregressive behavior.
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1. Algorithmic Approaches to Output Prediction in a Virtual Power Plant
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Virtual Power Plants (VPPs) are an emerging form of technology that allows owners of electricity producing appliances, such as electric vehicles, to partake in a pool of producers of sustainable energy. The Swedish electricity grid owner Svenska Kraftnät hosts a platform where VPPs act as intermediaries between energy producing customers and third party buyers. READ MORE
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2. Parameter Update Schemes for Hidden Markov Models applied to Financial Returns
University essay from Lunds universitet/Matematisk statistikAbstract : This thesis was dedicated to investigating the use of different parameter update schemes for Hidden Markov models with time-varying parameters, with an emphasis on developing alternatives to the quasi-Newton step. The focus was on applications to financial returns, using data from the S\&P-500 and the Nikkei index, and for comparison, a trial using synthetic data was also performed. READ MORE
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3. Multivariate Time Series Prediction for DevOps : A first Step to Fault Prediction of the CI Infrastructure
University essay from Linköpings universitet/Statistik och maskininlärningAbstract : The continuous integration infrastructure (CI servers) is commonly used as a shared test environment due to the need for collaborative and distributive development for the software products under growing scale and complexity in recent years. To ensure the stability of the CI servers, with the help of the constantly recorded measurement data of the servers, fault prediction is of great interest to software development companies. READ MORE
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4. Time-series Generative Adversarial Networks for Telecommunications Data Augmentation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Time- series Generative Adversarial Networks (TimeGAN) is proposed to overcome the GAN model’s insufficiency in producing synthetic samples that inherit the predictive ability of the original timeseries data. TimeGAN combines the unsupervised adversarial loss in the GAN framework with a supervised loss adopted from an autoregressive model. READ MORE
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5. LSTM Neural Network Models for Market Movement Prediction
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Interpreting time varying phenomena is a key challenge in the capital markets. Time series analysis using autoregressive methods has been carried out over the last couple of decades, often with reassuring results. READ MORE