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Short term electric load forecasting using an adaptively trained layered perceptron

机译:使用自适应培训的层次训练的扫描预测短期电负荷预测

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The authors address electric load forecasting using artificial neural network (NN) technology. They summarize research for Puget Sound Power and Light Company. In this study, several structures for NNs are proposed and tested. Features extraction is implemented to capture strongly correlated variables to electric loads. The NN is compared to several forecasting models. Most of them are commercial codes. The NN performed as well as the best and most sophisticated commercial forecasting systems.
机译:作者使用人工神经网络(NN)技术来解决电力负荷预测。他们总结了Puget Sound Power和Light Company的研究。在这项研究中,提出并测试了NNS的几种结构。实施特征提取以捕获强烈相关的变量与电负载。将NN与几个预测模型进行比较。他们中的大多数是商业代码。 NN执行了最佳,最复杂的商业预测系统。

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