Hybrid energy storage systems and control strategies for stand-alone renewable energy power systems
LW Chong, YW Wong, RK Rajkumar… - … and sustainable energy …, 2016 - Elsevier
The energy storage system (ESS) in a conventional stand-alone renewable energy power
system (REPS) usually has a short lifespan mainly due to irregular output of renewable …
system (REPS) usually has a short lifespan mainly due to irregular output of renewable …
Current status of wind energy forecasting and a hybrid method for hourly predictions
I Okumus, A Dinler - Energy Conversion and Management, 2016 - Elsevier
Generating accurate wind energy and/or power forecasts is crucially important for energy
trading and planning. The present study initially gives an extensive review of recent …
trading and planning. The present study initially gives an extensive review of recent …
Convolutional neural network-based deep transfer learning for fault detection of gas turbine combustion chambers
Gas turbine combustion chambers work in highly adverse environment and thus malfunction
more easily compared to other components. Fault detection of gas turbine combustion …
more easily compared to other components. Fault detection of gas turbine combustion …
[HTML][HTML] A hybrid spectral clustering and deep neural network ensemble algorithm for intrusion detection in sensor networks
T Ma, F Wang, J Cheng, Y Yu, X Chen - Sensors, 2016 - mdpi.com
The development of intrusion detection systems (IDS) that are adapted to allow routers and
network defence systems to detect malicious network traffic disguised as network protocols …
network defence systems to detect malicious network traffic disguised as network protocols …
A novel transfer learning approach for wind power prediction based on a serio-parallel deep learning architecture
H Yin, Z Ou, J Fu, Y Cai, S Chen, A Meng - Energy, 2021 - Elsevier
Although machine learning methods have been widely applied in the wind power prediction
field, they are not suitable for building the prediction model of a new-built wind farm because …
field, they are not suitable for building the prediction model of a new-built wind farm because …
Software defect prediction using stacked denoising autoencoders and two-stage ensemble learning
H Tong, B Liu, S Wang - Information and Software Technology, 2018 - Elsevier
Context Software defect prediction (SDP) plays an important role in allocating testing
resources reasonably, reducing testing costs, and ensuring software quality. However …
resources reasonably, reducing testing costs, and ensuring software quality. However …
Transferability improvement in short-term traffic prediction using stacked LSTM network
Short-term traffic flow forecasting is a key element in Intelligent Transport Systems (ITS) to
provide proactive traffic state information to road network operators. A variety of methods to …
provide proactive traffic state information to road network operators. A variety of methods to …
Application of hybrid model based on double decomposition, error correction and deep learning in short-term wind speed prediction
As wind power accounts for an increasing proportion of the electricity market, the wind
speed prediction plays a vital role in the stable operation of the power grid. However, owing …
speed prediction plays a vital role in the stable operation of the power grid. However, owing …
Transfer learning based multi-layer extreme learning machine for probabilistic wind power forecasting
Y Liu, J Wang - Applied Energy, 2022 - Elsevier
With the increasing penetration of wind power, probabilistic forecasting becomes critical to
quantifying wind power uncertainties and guiding power system operations. This paper …
quantifying wind power uncertainties and guiding power system operations. This paper …
A survey on time-series pre-trained models
Time-Series Mining (TSM) is an important research area since it shows great potential in
practical applications. Deep learning models that rely on massive labeled data have been …
practical applications. Deep learning models that rely on massive labeled data have been …