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[HTML][HTML] Systematic review on impact of different irradiance forecasting techniques for solar energy prediction
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 …
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
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 …
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
Traffic prediction is crucial for transportation management and user convenience. With the
rapid development of deep learning techniques, numerous models have emerged for traffic …
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
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 …
disturbances in the body. Diabetes is mainly treated clinically by conservative treatment …
Towards dynamic spatial-temporal graph learning: A decoupled perspective
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 …
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 …
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 …
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
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 …
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
Traffic flow prediction plays an instrumental role in modern intelligent transportation systems.
Numerous existing studies utilize inter-embedded fusion routes to extract the intrinsic …
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 …
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
Climate variability, trend analysis, and accurate forecasting are vital in a country's effective
water resource management and strategic planning. Precipitation and temperature are …
water resource management and strategic planning. Precipitation and temperature are …