USING LSTM NETWORK FOR SOLVING THE MULTIDIMENTIONAL TIME SERIES FORECASTING PROBLEM

M. Obrubov, S. Kirillova
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引用次数: 2

Abstract

The article discusses using of the recurrent neural networks technology to the multidimensional time series prediction problem. There is an experimental determination of the neural network architecture and its main hyperparameters carried out to achieve the minimum error. The revealed network structure going to be used further to detect anomalies in multidimensional time series.
利用LSTM网络解决了多维时间序列预测问题
本文讨论了递归神经网络技术在多维时间序列预测问题中的应用。为了实现最小误差,对神经网络的结构和主要超参数进行了实验确定。所揭示的网络结构将进一步用于检测多维时间序列中的异常。
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