LDR | | 00000nmm u2200205 4500 |
001 | | 000000332927 |
005 | | 20241206155136 |
008 | | 181129s2018 ||| | | | eng d |
020 | |
▼a 9780438323834 |
035 | |
▼a (MiAaPQ)AAI10793389 |
035 | |
▼a (MiAaPQ)berkeley:17729 |
040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
049 | 1 |
▼f DP |
082 | 0 |
▼a 620 |
100 | 1 |
▼a Lin, Ziheng. |
245 | 10 |
▼a Recurrent Neural Network Models of Human Mobility. |
260 | |
▼a [S.l.] :
▼b University of California, Berkeley.,
▼c 2018 |
260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
300 | |
▼a 78 p. |
500 | |
▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B. |
500 | |
▼a Adviser: Alexei Pozdnukhov. |
502 | 1 |
▼a Thesis (Ph.D.)--University of California, Berkeley, 2018. |
520 | |
▼a Locational data generated by mobile devices present an opportunity to substantially simplify methodologies and reduce analysis latencies in short-term transportation planning applications. Short-term transportation planning, such as traffic flow |
590 | |
▼a School code: 0028. |
650 | 4 |
▼a Engineering. |
650 | 4 |
▼a Transportation. |
690 | |
▼a 0537 |
690 | |
▼a 0709 |
710 | 20 |
▼a University of California, Berkeley.
▼b Civil and Environmental Engineering. |
773 | 0 |
▼t Dissertation Abstracts International
▼g 80-01B(E). |
773 | |
▼t Dissertation Abstract International |
790 | |
▼a 0028 |
791 | |
▼a Ph.D. |
792 | |
▼a 2018 |
793 | |
▼a English |
856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997750
▼n KERIS |
980 | |
▼a 201812
▼f 2019 |
990 | |
▼a 관리자
▼b 관리자 |