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Prediction of hourly energy consumption in buildings based on a feedback artificial neural network

机译:基于反馈人工神经网络的建筑物小时能耗预测

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In this paper a new approach for short-term load prediction in buildings is shown. The method is based on a special kind of artificial neural network (ANN), which feeds back a part of its outputs. This ANN is trained by means of a hybrid algorithm. The new system uses current and forecasted values of temperature, the current load and the hour and the day as inputs. The performance of this predictor was evaluated using real data and results from international contests. The achieved results demonstrate the high precision reached with this system.
机译:本文展示了一种用于建筑物中短期负荷预测的新方法。该方法基于一种特殊的人工神经网络(ANN),它可以反馈部分输出。通过混合算法训练该人工神经网络。新系统使用温度的当前值和预测值,当前负载以及小时和天作为输入。使用真实数据和国际比赛的结果来评估此预测变量的性能。所获得的结果证明了该系统的高精度。

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