In this paper, we elaborate over the well-known interpretability issue in echo-state networks
(ESNs). The idea is to investigate the dynamics of reservoir neurons with time-series …

In this paper, energy consumption of an office building is predicted based on echo state
networks (ESNs). Energy consumption of the office building is divided into consumptions …

This paper proposes a new echo state network (ESN) with variable memory length. For input-
driven applications, existing ESNs do not fully consider the characteristics of input signals …

Echo state networks (ESNs) have been widely used in the field of time series prediction. In
conventional ESNs, the spectral radius of reservoir is always scaled to lower than 1 to satisfy …

Anomaly detection is a very effective method to extract useful information from abundant
data. Most existing anomaly detection methods are based on normal region or some specific …

Preventive maintenance through predicting the Remaining Useful Life (RUL) of engineering
components is considered as a breakthrough in Industry4. 0. Researchers are developing …

Echo state network (ESN) has gained wide acceptance in the field of time series prediction,
relying on sufficiently complex reservoir connections to remember the historical features of …

Office buildings commonly contain such room types as office rooms, server rooms, storage
rooms, meeting rooms, etc., while the power consumption inside the rooms generally comes …

The field of Prognostics and Health Management (PHM) in industries is gaining greater
popularity to achieve high reliability by shifting the preventive maintenance to predictive …

With the development of nonlinear science, improving the prediction performance of chaotic
time series is of great significance in industrial production and daily life. Now, researchers …