Hydrological series data are non-stationary and nonlinear. However, certain data-driven forecasting methods assume that streamflow stable, which contradicts reality causes the simulated value to deviate from observed one. Ensemble empirical mode decomposition (EEMD) was employed in this study decompose runoff into several stationary components a trend. The long short-term memory (LSTM) model us...

Harmonic detection and control for power grids have always been major concerns researchers. With the application of diverse semiconductor materials in systems, numerous asymmetrical loads arise, resulting increasingly poor performance traditional harmonic methods. Ensemble empirical mode decomposition (EEMD) provides a new approach systems. Because waves systems are indeterminate, optimal resul...

quantification of arterial elasticity and its dependency to age is considered in this paper. we use radiofrequency (rf) signals fromcarotid artery ultasonography to evaluate this dependency. blood pressure, blood flow, and tethering to surrounding tissue are the maincauses of the motion of the carotid wall. tracking carotid artery wall motion from a series of ultrasound b‑mode images is challen...

Accurate and reliable forecasts of diarrhea incidences are necessary for the health authorities to ensure the appropriate action for the control of the outbreak. In this paper, a novel hybrid model known as EEMD-GRNN is proposed to forecast the diarrhea incidences. The proposed approach first uses Ensemble Empirical Mode Decomposition (EEMD), which can adaptively decompose the complicated raw t...

based on the problems caused by today conventional vehicles, much attention has been put on the fuel cell vehicles researches. however, using a fuel cell system is not adequate alone in transportation applications, because the load power profile includes transient that is not compatible with the fuel cell dynamic. to resolve this problem, hybridization of the fuel cell and energy storage device...

A new blind source separation method is proposed to solve the single-channel mechanical signal separation. The new approach consists of ensemble ensemble empirical mode decomposition (EEMD) and blind source separation. Firstly the single-channel signal was decomposed into a set of proper intrinsic mode functions(IMF) by EEMD. A multi-dimensional signal was obtained by the combination of the den...