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More and more power plants have been constructed and generated by intermittent energy. As a clean and renewable energy, such sources as wind and solar are favored in the new generation of power grid system. However, influenced by factors of geography, circumstance and climates, the renewable energy has the characteristics of intermittency, volatility and uncontrollability, which reduce the efficient...
Today, big data is not only the data scenario with large volume, but also high-speed and changing all the time. Such data streams commonly exist in Smart Grid facilities. Decision tree as one of the most widely-used analysis methods, has been applied in the decision support system for smart grid. This paper proposes a two-level classifier combining cache-based classifier and incremental decision tree...
Decision tree, as one of the most widely used methods in data mining, has been used in many realistic application. Incremental decision tree handles streaming data scenario that is applicable for big data analysis. However, imperfect data are unavoidable in real-world applications. Studying the state-of-art incremental decision tree induction using Hoeffding bound, we investigated the influence of...
How to efficiently uncover the knowledge hidden within massive and big data remains an open problem. One of the challenges is the issue of 'concept drift' in streaming data flows. Concept drift is a well-known problem in data analytics, in which the statistical properties of the attributes and their target classes shift over time, making the trained model less accurate. Many methods have been proposed...
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