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Critical analysis of pattern recognition load curves using multi-layer perceptron neural network

机译:基于多层感知器神经网络的模式识别负载曲线的临界分析

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Understanding energy consumption patterns is a very important task for a good operation of power system, such patterns can be studied through the history of load curves of a given system. In this study is proposed a methodology for classification of load curves based on the similarities of the patterns presented over the days of the week in which they were generated. For this, a Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN) was used to perform the pattern recognition of load curves. The results show that the algorithm was able to find typical behaviors in the set of analyzed curves, classifying curves with similar patterns in matching groups.
机译:理解能耗模式对于电力系统的良好运行是一项非常重要的任务,可以通过给定系统的负载曲线的历史来研究这种模式。在这项研究中,提出了一种基于负荷曲线在一周中几天内呈现的模式的相似性进行分类的方法。为此,使用了多层感知器(MLP)人工神经网络(ANN)来执行载荷曲线的模式识别。结果表明,该算法能够在一组分析曲线中找到典型行为,并在匹配组中对具有相似模式的曲线进行分类。

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