[HTML][HTML] Advanced series decomposition with a gated recurrent unit and graph convolutional neural network for non-stationary data patterns

H Han, H Neira-Molina, A Khan, M Fang… - Journal of Cloud …, 2024 - Springer
In this study, we present the EEG-GCN, a novel hybrid model for the prediction of time series
data, adept at addressing the inherent challenges posed by the data's complex, non-linear …

An Improved Artificial Potential Field Method for Ship Path Planning Based on Artificial Potential Field—Mined Customary Navigation Routes

Y Suo, X Chen, J Yue, S Yang… - Journal of Marine Science …, 2024 - mdpi.com
In recent years, the artificial potential field has garnered significant attention in ship route
planning and traffic flow simulation. However, the traditional artificial potential field method …

STVANet: A spatio-temporal visual attention framework with large kernel attention mechanism for citywide traffic dynamics prediction

H Yang, J Jiang, Z Zhao, R Pan, S Tao - Expert Systems with Applications, 2024 - Elsevier
Enhancing the efficiency and safety of the Intelligent Transportation System requires
effective modeling and prediction of citywide traffic dynamics. Most studies employ …

Traffic Prediction with Self-Supervised Learning: A Heterogeneity-Aware Model for Urban Traffic Flow Prediction Based on Self-Supervised Learning

M Gao, Y Wei, Y Xie, Y Zhang - Mathematics, 2024 - mdpi.com
Accurate traffic prediction is pivotal when constructing intelligent cities to enhance urban
mobility and to efficiently manage traffic flows. Traditional deep learning-based traffic …

Construction of Short-Term Traffic Flow Prediction Model Based on IoT and Deep Learning Algorithms.

X Sun, H Dou - … Journal of Advanced Computer Science & …, 2024 - search.ebscohost.com
On a global scale, traffic problems are an essential factor affecting urban operations,
particularly challenging the frequent occurrence of traffic congestion and accidents. The …