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    • 4. 发明申请
    • Profiling Energy Consumption
    • 分析能源消耗
    • US20130124436A1
    • 2013-05-16
    • US13297033
    • 2011-11-15
    • Alvaro A. Cardenas MoraDaisuke Mashima
    • Alvaro A. Cardenas MoraDaisuke Mashima
    • G06N5/04G06F15/18
    • G06F17/18
    • Embodiments for detecting anomalous consumption of energy are provided. Information associated with energy consumption over a designated period of time is received. A threshold value is received. A classifier based on an Auto-Regressive Moving Average model is applied to the information and a result representing the likelihood of an attack is determined. The result is then analyzed to determine if it attained a threshold value. The information is then classified as indicating an attack. Additionally, embodiments for utilizing machine learning to train a classifier using training data to develop parameters for the auto-regressive moving average model are provided. Further, embodiments for evaluating the effectiveness of the parameters used in the Auto-Regressive Moving Average model to classify data are provided.
    • 提供了用于检测能量异常消耗的实施例。 收到与指定时间段内的能源消耗相关的信息。 接收到一个阈值。 基于自回归移动平均模型的分类器被应用于信息,并且表示确定攻击的可能性的结果。 然后分析结果以确定其是否达到阈值。 然后将信息分类为指示攻击。 此外,提供了利用机器学习来训练分类器的实施例,其使用训练数据来开发用于自回归移动平均模型的参数。 此外,提供了用于评估在自回归移动平均模型中用于对数据进行分类的参数的有效性的实施例。