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Recurrent neural networks and load forecasting

机译:经常性神经网络和负载预测

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摘要

The ability of a recurrent network to model load forecasting is investigated. Its performance in a competition is then contrasted with that of feedforward networks and linear models. Its weaknesses and strengths are then analyzed to give guidelines to the design of neural net predictors with the hope of designing better predictors in the future.
机译:调查了经常性网络对装载预测的能力进行了研究。其在竞争中的性能与前馈网络和线性模型的表现形成鲜明对比。然后分析了其弱点和优势,向神经净预测因子设计有指导,希望未来设计更好的预测因子。

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