9、Building Energy Load Forecasting using Deep Neural Networks
亮点：考虑了LSTM和S2S的不同层结构对训练和测试集的结构影响。 基于深度神经网络的建筑能量负荷预测网络 所介绍的工作调查了两个LSTM基础架构：1）标准LSTM和2）基于LSTM序列到序列（S2S）架构。 两种方法都是在电力消耗的基准数据集上实施来自一个住宅客户的数据。 这两种架构都是经过一小时一分钟的训练和测试分辨率数据集。 表明标准LSTM在一分钟分辨率数据时失败在一小时的分辨率数据中
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相关文章
- 1. 3 Deep Neural Networks for Energy Load Forecasting
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