Multispans: A multi-range spatial-temporal transformer network for traffic forecast via structural entropy optimization
Traffic forecasting is a complex multivariate time-series regression task of paramount
importance for traffic management and planning. However, existing approaches often …
importance for traffic management and planning. However, existing approaches often …
[HTML][HTML] Developing deep learning surrogate models for digital twins in mineral processing–A case study on data-driven multivariate multistep forecasting
A Zeb, J Linnosmaa, M Seppi, O Saarela - Minerals Engineering, 2024 - Elsevier
The escalating demand for environmental and social sustainability underscores the critical
need for large industries such as mining and metallurgy to function optimally. Achieving …
need for large industries such as mining and metallurgy to function optimally. Achieving …
Gmad: multivariate time series anomaly detection based on graph matching learning
The graph neural network-based model aims to explore the interaction patterns between
sequences in multivariate time series anomaly detection. Current approach pursues …
sequences in multivariate time series anomaly detection. Current approach pursues …
Extended random forest for multivariate air quality forecasting
H mirzadeh, H omranpour - International Journal of Machine Learning and …, 2024 - Springer
In this research, an extended random forest algorithm for multivariate time series several
steps forecasting is proposed. Peoposed method consists input layer and hidden layers …
steps forecasting is proposed. Peoposed method consists input layer and hidden layers …