A survey on intelligent Internet of Things: Applications, security, privacy, and future directions
The rapid advances in the Internet of Things (IoT) have promoted a revolution in
communication technology and offered various customer services. Artificial intelligence (AI) …
communication technology and offered various customer services. Artificial intelligence (AI) …
Vessel trajectory prediction in maritime transportation: Current approaches and beyond
The growing availability of maritime IoT traffic data and continuous expansion of the
maritime traffic volume, serving as the driving fuel, propel the latest Artificial Intelligence (AI) …
maritime traffic volume, serving as the driving fuel, propel the latest Artificial Intelligence (AI) …
Multi-step-ahead wind speed forecasting based on a hybrid decomposition method and temporal convolutional networks
Recently, the boom in wind power industry has called for the accurate and stable wind
speed forecasting, on which reliable wind power generation systems depend heavily. Due to …
speed forecasting, on which reliable wind power generation systems depend heavily. Due to …
A hybrid prediction method for realistic network traffic with temporal convolutional network and LSTM
Accurate and real-time prediction of network traffic can not only help system operators
allocate resources rationally according to their actual business needs but also help them …
allocate resources rationally according to their actual business needs but also help them …
A novel multi-scale CNN and attention mechanism method with multi-sensor signal for remaining useful life prediction
X Xu, X Li, W Ming, M Chen - Computers & Industrial Engineering, 2022 - Elsevier
Remaining useful life prediction is crucial in smart manufacturing systems due to many
advantages of early prognostics, ie, downtime reduction, service time prolongation, ultimate …
advantages of early prognostics, ie, downtime reduction, service time prolongation, ultimate …
A robust deep learning framework for short-term wind power forecast of a full-scale wind farm using atmospheric variables
Short-term (less than 1 h) forecast of the power generated by wind turbines in a wind farm is
extremely challenging due to the lack of reliable data from meteorological towers and …
extremely challenging due to the lack of reliable data from meteorological towers and …
State of charge estimation of lithium-ion batteries based on temporal convolutional network and transfer learning
Y Liu, J Li, G Zhang, B Hua, N Xiong - Ieee Access, 2021 - ieeexplore.ieee.org
Accurate estimation of the state of charge (SOC) is critical for the normal use of lithium-ion
battery equipment like electric vehicles. However, the SOC of lithium-ion battery is not …
battery equipment like electric vehicles. However, the SOC of lithium-ion battery is not …
Dynamic hypergraph structure learning for traffic flow forecasting
This paper studies the problem of traffic flow forecasting, which aims to predict future traffic
conditions on the basis of road networks and traffic conditions in the past. The problem is …
conditions on the basis of road networks and traffic conditions in the past. The problem is …
Deep learning for road traffic forecasting: Does it make a difference?
Deep Learning methods have been proven to be flexible to model complex phenomena.
This has also been the case of Intelligent Transportation Systems, in which several areas …
This has also been the case of Intelligent Transportation Systems, in which several areas …
State of charge estimation for lithium-ion batteries based on TCN-LSTM neural networks
C Hu, F Cheng, L Ma, B Li - Journal of the Electrochemical …, 2022 - iopscience.iop.org
Accurately estimating the state of charge (SOC) of lithium-ion batteries is critical for
developing more reliable and efficient operation of electric vehicles. However, the commonly …
developing more reliable and efficient operation of electric vehicles. However, the commonly …