Parallel spatio-temporal attention-based TCN for multivariate time series prediction
J Fan, K Zhang, Y Huang, Y Zhu, B Chen - Neural Computing and …, 2023 - Springer
As industrial systems become more complex and monitoring sensors for everything from
surveillance to our health become more ubiquitous, multivariate time series prediction is …
surveillance to our health become more ubiquitous, multivariate time series prediction is …
[HTML][HTML] Systematic review of energy theft practices and autonomous detection through artificial intelligence methods
E Stracqualursi, A Rosato, G Di Lorenzo… - … and Sustainable Energy …, 2023 - Elsevier
Energy theft poses a significant challenge for all parties involved in energy distribution, and
its detection is crucial for maintaining stable and financially sustainable energy grids. One …
its detection is crucial for maintaining stable and financially sustainable energy grids. One …
Deep learning-powered vessel trajectory prediction for improving smart traffic services in maritime Internet of Things
The maritime Internet of Things (IoT) has recently emerged as a revolutionary
communication paradigm where a large number of moving vessels are closely …
communication paradigm where a large number of moving vessels are closely …
BAT: Deep learning methods on network intrusion detection using NSL-KDD dataset
T Su, H Sun, J Zhu, S Wang, Y Li - IEEE Access, 2020 - ieeexplore.ieee.org
Intrusion detection can identify unknown attacks from network traffics and has been an
effective means of network security. Nowadays, existing methods for network anomaly …
effective means of network security. Nowadays, existing methods for network anomaly …
Application of wavelet-packet transform driven deep learning method in PM2. 5 concentration prediction: A case study of Qingdao, China
Q Zheng, X Tian, Z Yu, N Jiang, A Elhanashi… - Sustainable Cities and …, 2023 - Elsevier
Air pollution is one of the most serious environmental problems faced by human beings, and
it is also a hot topic in the development of sustainable cities. Accurate PM 2.5 prediction …
it is also a hot topic in the development of sustainable cities. Accurate PM 2.5 prediction …
Age of information aware radio resource management in vehicular networks: A proactive deep reinforcement learning perspective
In this paper, we investigate the problem of age of information (AoI)-aware radio resource
management for expected long-term performance optimization in a Manhattan grid vehicle …
management for expected long-term performance optimization in a Manhattan grid vehicle …
Artificial intelligence modelling integrated with Singular Spectral analysis and Seasonal-Trend decomposition using Loess approaches for streamflow predictions
The nature of streamflow in the basins is stochastic and complex making it difficult to make
an accurate prediction about the future river flows. Recently, artificial neural-based deep …
an accurate prediction about the future river flows. Recently, artificial neural-based deep …
Daily traffic flow forecasting through a contextual convolutional recurrent neural network modeling inter-and intra-day traffic patterns
Traffic flow forecasting is an important problem for the successful deployment of intelligent
transportation systems, which has been studied for more than two decades. In recent years …
transportation systems, which has been studied for more than two decades. In recent years …
Short-term load forecasting based on CEEMDAN and Transformer
P Ran, K Dong, X Liu, J Wang - Electric Power Systems Research, 2023 - Elsevier
Short-term load forecasting (STLF) is an essential part of energy plan, and it is very
meaningful for energy management. Recently, some deep learning models have been …
meaningful for energy management. Recently, some deep learning models have been …
The LSTM-based advantage actor-critic learning for resource management in network slicing with user mobility
Network slicing aims to efficiently provision diversified services with distinct requirements
over the same physical infrastructure. Therein, in order to efficiently allocate resources …
over the same physical infrastructure. Therein, in order to efficiently allocate resources …