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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 ...
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 ...
Time Series Forecasting Using Online Performance-based Ensemble Deep Random Vector Functional Link Neural Network
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Time series forecasting remains a challenging task in data science while it is of great relevance to decision-making in various industries such as transportation, finance, electricity resource management, meteorology. ...
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 ...
Situation Awareness Recognition Using EEG and Eye-Tracking data: a pilot study
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Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Since situation awareness (SA) plays an important role in many fields, the measure of SA is one of the most concerning problems. Using physiological signals to evaluate SA is becoming a popular research topic because of ...
Deep Reservoir Computing Based Random Vector Functional Link for Non-sequential Classification
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Reservoir Computing (RC) is well-suited for simpler sequential tasks which require inexpensive, rapid training, and the Echo State Network (ESN) plays a significant role in RC. In this article, we proposed variations of ...