1 citations · 1 across the 3 of their papers we have counts for
3 papers
A comparative study of deep learning and ensemble learning to extend the horizon of traffic forecasting
Xiao Zheng, Saeed Asadi Bagloee, Majid Sarvi
Traffic forecasting is vital for Intelligent Transportation Systems, for which Machine Learning (ML) methods have been extensively explored to develop data-driven Artificial Intell…
Spatial-temporal Forecasting for Regions without Observations
Xinyu Su, Jianzhong Qi, Egemen Tanin +2
Spatial-temporal forecasting plays an important role in many real-world applications, such as traffic forecasting, air pollutant forecasting, crowd-flow forecasting, and so on. Sta…
μ-DDRL: A QoS-Aware Distributed Deep Reinforcement Learning Technique for Service Offloading in Fog computing Environments
Mohammad Goudarzi, Maria A. Rodriguez, Majid Sarvi +1
Fog and Edge computing extend cloud services to the proximity of end users, allowing many Internet of Things (IoT) use cases, particularly latency-critical applications. Smart devi…