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pro vyhledávání: '"Fischer, Ulrike"'
Autor:
Fischer, Ulrike, Lehner, Wolfgang
Whereas traditional data warehouse systems assume that data is complete or has been carefully preprocessed, increasingly more data is imprecise, incomplete, and inconsistent. This is especially true in the context of big data, where massive amount of
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https://tud.qucosa.de/id/qucosa%3A83284
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Forecasting time series data is crucial in a number of domains such as supply chain management and display advertisement. In these areas, the time series data to forecast is typically organized along multiple dimensions leading to a high number of ti
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https://tud.qucosa.de/id/qucosa%3A81890
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Autor:
Dannecker, Lars, Rösch, Philipp, Fischer, Ulrike, Gaumnitz, Gordon, Lehner, Wolfgang, Hackenbroich, Gregor
Continuous balancing of energy demand and supply is a fundamental prerequisite for the stability of energy grids and requires accurate forecasts of electricity consumption and production at any point in time. Today's Energy Data Management (EDM) syst
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https://tud.qucosa.de/id/qucosa%3A80643
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The integration of renewable energy sources (RES) into local energy distribution networks becomes increasingly important. Renewable energy highly depends on weather conditions, making it difficult to maintain stability in such networks. To still enab
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https://tud.qucosa.de/id/qucosa%3A80639
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Integrating sophisticated statistical methods into database management systems is gaining more and more attention in research and industry. One important statistical method is time series forecasting, which is crucial for decision management in many
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https://tud.qucosa.de/id/qucosa%3A83109
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Forecasts are important to decision-making and risk assessment in many domains. Since current database systems do not provide integrated support for forecasting, it is usually done outside the database system by specially trained experts using foreca
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https://tud.qucosa.de/id/qucosa%3A81729
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Time series forecasting is challenging as sophisticated forecast models are computationally expensive to build. Recent research has addressed the integration of forecasting inside a DBMS. One main benefit is that models can be created once and then r
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https://tud.qucosa.de/id/qucosa%3A80647
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Autor:
Böhm, Matthias, Dannecker, Lars, Doms, Andreas, Dovgan, Erik, Filipič, Bogdan, Fischer, Ulrike, Lehner, Wolfgang, Pedersen, Torben Bach, Pitarch, Yoann, Šikšnys, Laurynas, Tušar, Tea
Nowadays, Renewable Energy Sources (RES) are attracting more and more interest. Thus, many countries aim to increase the share of green energy and have to face with several challenges (e.g., balancing, storage, pricing). In this paper, we address the
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https://tud.qucosa.de/id/qucosa%3A79774
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https://tud.qucosa.de/api/qucosa%3A79774/attachment/ATT-0/
Forecasts are important to decision-making and risk assessment in many domains. There has been recent interest in integrating forecast queries inside a DBMS. Answering a forecast query requires the creation of forecast models. Creating a forecast mod
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https://tud.qucosa.de/id/qucosa%3A80545
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Quality control using scalar quality measures is standard practice in manufacturing. However, there are also quality measures that are determined at a large number of positions on a product, since the spatial distribution is important. We denote such
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https://tud.qucosa.de/id/qucosa%3A81358
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