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Use of ANN for identification of consumers with irregular electrical installations

机译:使用ANN识别具有不规则电气安装的消费者

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This paper presents the results obtained with artificial intelligence techniques applied to identify consumers with irregular installations in the electrical distribution system. A multilayer perceptron artificial neural network was used, with 10 neurons in the hidden layer, sigmoid activation function and backpropagation algorithm for training. Information typically available for electric power distribution companies were used as input data. The results obtained showed a success rate of up to 67.5%, which can be considered high when compared to analytical techniques commonly used by power distribution companies, whose success rate is between 25% and 30%. By the end it is possible to conclude that the use of the presented technic may be very useful for power distribution companies while reducing nontechnical losses of electric energy.
机译:本文介绍了通过人工智能技术获得的结果,这些技术用于识别配电系统中不规则安装的消费者。使用了多层感知器人工神经网络,在隐藏层中具有10个神经元,并采用了S型激活函数和反向传播算法进行训练。配电公司通常可获得的信息用作输入数据。获得的结果显示成功率高达67.5%,与配电公司通常使用的分析技术(其成功率在25%至30%之间)相比,可以认为是很高的。到最后,可以得出的结论是,所介绍的技术对配电公司可能非常有用,同时减少了非技术性的电能损耗。

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