Abstract Gross domestic product estimation based on electricity utilization by artificial neural network
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Gross domestic product estimation based on electricity utilization by artificial neural network

机译:基于人工神经网络电力利用的国内生产总值估算

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Abstract The main goal of the paper was to estimate gross domestic product (GDP) based on electricity estimation by artificial neural network (ANN). The electricity utilization was analyzed based on different sources like renewable, coal and nuclear sources. The ANN network was trained with two training algorithms namely extreme learning method and back-propagation algorithm in order to produce the best prediction results of the GDP. According to the results it can be concluded that the ANN model with extreme learning method could produce the acceptable prediction of the GDP based on the electricity utilization. Highlights ? To estimate gross domestic product (GDP) based on electricity estimation. ? The electricity utilization was analyzed based on different sources. ? ANN model wit
机译:<![cdata [ Abstract 本文的主要目标是根据人工神经网络(ANN)的电力估算来估计国内生产总值(GDP)。基于可再生,煤炭和核来源等不同来源分析了电力利用。 ANN网络接受了两个训练算法,即极端学习方法和背传播算法,以产生GDP的最佳预测结果。根据结果​​,可以得出结论,具有极端学习方法的ANN模型可以基于电力利用产生GDP的可接受预测。 突出显示 以估算基于电力估计的国内生产总值(GDP)。 基于不同来源分析了电力利用率。 ANN模型机智

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