Name
Title | ||
|---|---|---|
Employing Machine Learning for Predicting Transportation Modes Under the COVID-19 Pandemic: A Mobility-Trends Analysis |
Abstract | ||
|---|---|---|
With the advent of Coronavirus Disease 2019 (COVID-19), the world encountered an unprecedented health crisis due to the severe acute respiratory syndrome (SARS) pathogen. This impacted all of the sectors but more critically the transportation sector which required a strategy in the light of mobility trends using transportation modes and regions. We analyse a mobility prediction model for smart tra... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/UCET54125.2021.9674960 | 2021 International Conference on UK-China Emerging Technologies (UCET) |
Keywords | DocType | ISBN |
Artificial Intelligence,COVID-19,Intelligent Transport Systems,Mobility Management,Travelers-Tracing | Conference | 978-1-6654-9575-2 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Syed Muhammad Asad | 1 | 0 | 1.01 |
| Kia Dashtipour | 2 | 0 | 1.01 |
| Rao Naveed Bin Rais | 3 | 0 | 0.34 |
| Sajjad Hussain | 4 | 0 | 1.35 |
| Qammer Hussain Abbasi | 5 | 0 | 0.68 |
| Muhammad Ali Imran | 6 | 2920 | 278.27 |