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Artificial neural networks for electricity consumption forecasting considering climatic factors

机译:考虑气候因素的人工神经网络用电量预测

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This work develops Artificial Neural Networks (ANN) models applied to predict the consumption forecasting considering climatic factors. It is intended to verify the influence of climatic factors on the electricity consumption forecasting through the ANN. The case study is applied in the Campinas city, Brazil. This work used Perceptron and Backpropagation ANN models. The specific goal is comparisons the performance of neural networks as an alternative to traditional forecasting methods. In this work were observed that despite direct or indirect influence of climatic factors on electricity consumption, a good prediction can be obtained using ANN without climatic factors.
机译:这项工作开发了人工神经网络(ANN)模型,用于考虑气候因素来预测消费量预测。旨在验证气候因素对通过人工神经网络预测的用电量的影响。案例研究在巴西坎皮纳斯市进行。这项工作使用了感知器和反向传播ANN模型。具体目标是比较神经网络作为传统预测方法的替代方法的性能。在这项工作中观察到,尽管气候因素对电力消耗有直接或间接的影响,但使用ANN可以在没有气候因素的情况下获得良好的预测。

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