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008181129s2018 ||| | | | eng d
020 ▼a 9780438323834
035 ▼a (MiAaPQ)AAI10793389
035 ▼a (MiAaPQ)berkeley:17729
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0491 ▼f DP
0820 ▼a 620
1001 ▼a Lin, Ziheng.
24510 ▼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.
5021 ▼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
71020 ▼a University of California, Berkeley. ▼b Civil and Environmental Engineering.
7730 ▼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
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14997750 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자 ▼b 관리자