Recurrent Neural Networks (RNNs) have demonstrated their outstanding ability in sequence
tasks and have achieved state-of-the-art in wide range of applications, such as industrial …

A recurrent neural network (RNN) has demonstrated its outstanding ability in sequence
tasks and has achieved state of the art in many applications, such as industrial and medical …

This article presents a comprehensively state-of-the-art investigation of the engineering
applications utilized by binary metaheuristic algorithms. Surveyed work is categorized based …

A novel method of using the spiking neural networks (SNNs) and the electroencephalograph
(EEG) processing techniques to recognize emotion states is proposed in this paper. Three …

In the field of Chronic disease prediction, identifying the relevant features plays an important
role for early disease diagnosis. With a high dimensionality of data, search for an adequate …

Due to the intermittent, fluctuating and random characteristics of wind system, the output of
wind power will become unstable with the change of wind, which brings severe challenges …

The effects of developing technology and rapid population growth on the environment have
been expanding gradually. Particularly, the growth in water consumption has revealed the …

Multiple reservoirs have been widely used in nonlinear time series forecasting. The hybrid
approach is recognized as the mainstream forecasting method in complex wind speed …

In this paper, considering the influence of multiple delayed output items on the prediction
accuracy of echo state network, a novel echo state network with multiple delayed outputs …

Medical decision making increasingly relies on machine learning algorithms to analyze
complex patient data and provide recommendations. However, the lack of interpretability in …