Essays about: "multivariate time series data"
Showing result 36 - 40 of 89 essays containing the words multivariate time series data.
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36. Time Series forecasting of the SP Global Clean Energy Index using a Multivariate LSTM
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Clean energy and machine learning are subjects that play significant roles in shaping our future. The current climate crisis has forced the world to take action towards more sustainable solutions. Arrangements such as the UN’s Sustainable Development Goals and the Paris Agreement are causing an increased interest in renewable energy solutions. READ MORE
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37. Multivariate Time Series Data Generation using Generative Adversarial Networks : Generating Realistic Sensor Time Series Data of Vehicles with an Abnormal Behaviour using TimeGAN
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Large datasets are a crucial requirement to achieve high performance, accuracy, and generalisation for any machine learning task, such as prediction or anomaly detection, However, it is not uncommon for datasets to be small or imbalanced since gathering data can be difficult, time-consuming, and expensive. In the task of collecting vehicle sensor time series data, in particular when the vehicle has an abnormal behaviour, these struggles are present and may hinder the automotive industry in its development. READ MORE
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38. Multivariate Short-term Electricity Load Forecasting with Deep Learning and exogenous covariates
University essay from Umeå universitet/Institutionen för tillämpad fysik och elektronikAbstract : Maintaining the electricity balance between supply and demand is a challenge for electricity suppliers. If there is an under or overproduction, it entails financial costs and affects consumers and the climate. To better understand how to maintain the balance, can the suppliers use short-term forecasts of electricity load. READ MORE
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39. Methods to combine predictions from ensemble learning in multivariate forecasting
University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Abstract : Making predictions nowadays is of high importance for any company, whether small or large, as thanks to the possibility to analyze the data available, new market opportunities can be found, risks and costs can be reduced, among others. Machine learning algorithms for time series can be used for predicting future values of interest. READ MORE
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40. Neural Ordinary Differential Equations for Anomaly Detection
University essay from KTH/Matematisk statistikAbstract : Today, a large amount of time series data is being produced from a variety of different devices such as smart speakers, cell phones and vehicles. This data can be used to make inferences and predictions. Neural network based methods are among one of the most popular ways to model time series data. READ MORE
