[HTML][HTML] Systematic review on impact of different irradiance forecasting techniques for solar energy prediction

K Sudharshan, C Naveen, P Vishnuram… - Energies, 2022 - mdpi.com
As non-renewable energy sources are in the verge of exhaustion, the entire world turns
towards renewable sources to fill its energy demand. In the near future, solar energy will be …

Temporal Convolutional Networks with RNN approach for chaotic time series prediction

HV Dudukcu, M Taskiran, ZGC Taskiran, T Yildirim - Applied soft computing, 2023 - Elsevier
The prediction of chaotic time series, which constitutes many systems in the field of science
and engineering, has recently become the focus of attention of researchers. Chaotic time …

[HTML][HTML] In-depth insights into the application of recurrent neural networks (rnns) in traffic prediction: A comprehensive review

Y He, P Huang, W Hong, Q Luo, L Li, KL Tsui - Algorithms, 2024 - mdpi.com
Traffic prediction is crucial for transportation management and user convenience. With the
rapid development of deep learning techniques, numerous models have emerged for traffic …

Short-term prediction method of blood glucose based on temporal multi-head attention mechanism for diabetic patients

G Yang, S Liu, Y Li, L He - Biomedical Signal Processing and Control, 2023 - Elsevier
The hyperglycemic state of people with diabetes can lead to metabolic and healthy
disturbances in the body. Diabetes is mainly treated clinically by conservative treatment …

Towards dynamic spatial-temporal graph learning: A decoupled perspective

B Wang, P Wang, Y Zhang, X Wang, Z Zhou… - Proceedings of the …, 2024 - ojs.aaai.org
With the progress of urban transportation systems, a significant amount of high-quality traffic
data is continuously collected through streaming manners, which has propelled the …

A deep attention-assisted and memory-augmented temporal convolutional network based model for rapid lithium-ion battery remaining useful life predictions with …

Z Fei, Z Zhang, F Yang, KL Tsui - Journal of Energy Storage, 2023 - Elsevier
Most of existing data-driven studies on lithium-ion battery remaining useful life (RUL)
prediction consider a large scope of cyclic data over the entire battery life. Yet, applications …

Digital twin for transportation big data: A reinforcement learning-based network traffic prediction approach

L Nie, X Wang, Q Zhao, Z Shang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular Ad-Hoc Networks (VANETs), as the crucial support of Intelligent Transportation
Systems (ITS), have received great attention in recent years. With the rapid development of …

GT-LSTM: A spatio-temporal ensemble network for traffic flow prediction

Y Luo, J Zheng, X Wang, Y Tao, X Jiang - Neural Networks, 2024 - Elsevier
Traffic flow prediction plays an instrumental role in modern intelligent transportation systems.
Numerous existing studies utilize inter-embedded fusion routes to extract the intrinsic …

Dynamic spatial–temporal graph convolutional recurrent networks for traffic flow forecasting

Z **a, Y Zhang, J Yang, L **e - Expert Systems with Applications, 2024 - Elsevier
Traffic flow forecasting is crucial for making appropriate route guidance and vehicle
scheduling schemes in intelligent transportation systems. However, recent graph-based …

[HTML][HTML] Time series trend analysis and forecasting of climate variability using deep learning in Thailand

M Waqas, UW Humphries, PT Hlaing - Results in Engineering, 2024 - Elsevier
Climate variability, trend analysis, and accurate forecasting are vital in a country's effective
water resource management and strategic planning. Precipitation and temperature are …