Essays about: "Time Series Data Generation"
Showing result 1 - 5 of 58 essays containing the words Time Series Data Generation.
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1. Land cover classification using machine-learning techniques applied to fused multi-modal satellite imagery and time series data
University essay from Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapAbstract : Land cover classification is one of the most studied topics in the field of remote sensing, involving the use of data from satellite sensors to analyze and categorize different land surface types. There are numerous satellite products available, each offering different spatial, spectral, and temporal resolutions. READ MORE
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2. Hosting Capacity Methods Considering Complementarity between Solar and Wind Power : A Case Study on a Swedish Regional Grid
University essay from Linköpings universitet/EnergisystemAbstract : The demand for electrical power is growing due to factors such as population growth, urbanisation, and the transition from fossil fuels to renewable energy sources. To be able to keep up with the changes in electricity demand, the Swedish power grid must connect more renewable power generation, but also increase its transmission capacity. READ MORE
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3. Cannibalization of Renewable Energy in Spain: Market Implications and Mitigation Strategies through CArbon Pricing and Gurarantess of Origin
University essay from KTH/Skolan för industriell teknik och management (ITM)Abstract : Renewable cannibalization refers to the phenomenon where the increasing penetration of zeromarginal cost renewable energy sources, such as solar and wind power, leads to a decline in their market value. By extension, this threatens to reduce investment incentives in wind and solar. READ MORE
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4. EVALUATING PERFORMANCE OF GENERATIVE MODELS FOR TIME SERIES SYNTHESIS
University essay from Mälardalens universitet/Akademin för innovation, design och teknikAbstract : Motivated by successes in the image generation domain, this thesis presents a novel Hybrid VQ-VAE (H-VQ-VAE) approach for generating realistic synthetic time series data with categorical features. The primary motivation behind this work is to address the limitations of existing generative models in accurately capturing the underlying structure and patterns of time series data, especially when dealing with categorical features. READ MORE
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5. Machine learning algorithm for generation and consumption forecasting in an electrical network
University essay from Mälardalens universitet/Akademin för innovation, design och teknikAbstract : Power generation and consumption are directly affected by weather, and the weather variables are fluctuating, which means that generation and consumption also fluctuate. These fluctuations can damage equipment or cause other problems in an electrical network. READ MORE
