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Significant wave height forecasting using hybrid ensemble deep randomized networks with neurons pruning
(
Elsevier Ltd
, 2023 , Article)
The reliable control of wave energy devices highly relies on the forecasts of wave heights. However, the dynamic characteristics and significant fluctuation of waves’ historical data pose challenges to precise predictions. ...
Dynamic ensemble deep echo state network for significant wave height forecasting
(
Elsevier Ltd
, 2023 , Article)
Forecasts of the wave heights can assist in the data-driven control of wave energy systems. However, the dynamic properties and extreme fluctuations of the historical observations pose challenges to the construction of ...
Graph ensemble deep random vector functional link network for traffic forecasting
(2022 , Article)
Traffic forecasting is crucial to achieving a smart city as it facilitates public transportation management, autonomous driving, and the resource relocation of the sharing economy. Traffic forecasting belongs to the ...
A decomposition-based hybrid ensemble CNN framework for driver fatigue recognition
(
Elsevier Inc.
, 2023 , Article)
Electroencephalogram (EEG) has become increasingly popular in driver fatigue monitoring systems. Several decomposition methods have been attempted to analyze the EEG signals that are complex, nonlinear and non-stationary ...
Automated layer-wise solution for ensemble deep randomized feed-forward neural network
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Elsevier B.V.
, 2022 , Article)
The randomized feed-forward neural network is a single hidden layer feed-forward neural network that enables efficient learning by optimizing only the output weights. The ensemble deep learning framework significantly ...
Inpatient Discharges Forecasting for Singapore Hospitals by Machine Learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Hospitals can predetermine the admission rate and facilitate resource allocation based on valid emergency requests and bed capacity estimation. The excess unoccupied beds can be determined with the help of forecasting the ...
EEG-based emotion recognition using random Convolutional Neural Networks
(
Elsevier Ltd
, 2022 , Article)
Emotion recognition based on electroencephalogram (EEG) signals is helpful in various fields, including medical healthcare. One possible medical application is to diagnose emotional disorders in patients. Humans tend to ...
Random vector functional link neural network based ensemble deep learning for short-term load forecasting
(
Elsevier Ltd
, 2022 , Article)
Electric load forecasting is essential for the planning and maintenance of power systems. However, its un-stationary and non-linear properties impose significant difficulties in predicting future demand. This paper proposes ...
An enhanced ensemble deep random vector functional link network for driver fatigue recognition
(
Elsevier
, 2023 , Article)
This work investigated the use of an ensemble deep random vector functional link (edRVFL) network for electroencephalogram (EEG)-based driver fatigue recognition. Against the low feature learning capability of the edRVFL ...