Random Hyper-parameter Search-Based Deep Neural Network for Power Consumption Forecasting
Abstract
In this paper, we introduce a deep learning approach, based on feed-forward neural networks, for big data time series forecasting with arbitrary prediction horizons. We firstly propose a random search to tune the multiple hyper-parameters involved in the method performance. There is a twofold objective for this search: firstly, to improve the forecasts and, secondly, to decrease the learning time. Next, we propose a procedure based on moving...
Paper Details
Title
Random Hyper-parameter Search-Based Deep Neural Network for Power Consumption Forecasting
Published Date
Jan 1, 2019
Journal
Pages
259 - 269
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