Name
Abstract | ||
|---|---|---|
Activity-based models in transport modeling and prediction are built from a large number of observed trips and their purposes. However, data acquired through traditional interview-based travel surveys is often inaccurate and insufficient. Recently, a human mobility sensing system, called Future Mobility Survey (FMS), was developed and used to collect travel data from more than 1,000 participants. ... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/MIS.2018.043741317 | IEEE Intelligent Systems |
Keywords | Field | DocType |
Frequency modulation,Quantization (signal),Activity recognition,Global Positioning System,Statistics | Data mining,Sensing system,Activity recognition,Computer science,Global Positioning System,Web application,Quantization (signal processing),TRIPS architecture,User interface,Ensemble learning | Journal |
Volume | Issue | ISSN |
33 | 4 | 1541-1672 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Youngsung Kim | 1 | 75 | 8.23 |
| Ajinkya Ghorpade | 2 | 6 | 1.47 |
| Fang Zhao | 3 | 6 | 2.14 |
| Francisco C. Pereira | 4 | 331 | 33.07 |
| P. Christopher Zegras | 5 | 6 | 1.47 |
| Moshe Ben-Akiva | 6 | 166 | 33.76 |