異常検知のためのDeep Echo State Networkによる工作機械センサデータの時系列予測

抄録

In this presentation, we present Deep Echo State Network （DeepESN）, which is suitable for time series prediction of sensor data during machining of machine tools. The recursive structure is built into each reservoir layer of DeepESN to improve the prediction accuracy of time series. In the experiment, we used Sunspot and MackeyGrass instead of machine tool sensor data, and compared the prediction accuracy of DeepESN with recursion structure, DeepESN without recursion structure, and LSTM.