Indexing, Querying, Prediction, and Integration for Network-constrained Moving Object Databases
Başlık:
Indexing, Querying, Prediction, and Integration for Network-constrained Moving Object Databases
Yazar:
Fouladgar, Mohammadhani, author.
ISBN:
9780438129177
Yazar Ek Girişi:
Fiziksel Tanımlama:
1 electronic resource (124 pages)
Genel Not:
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Advisors: Ramez Elmasri.
Özet:
The emergence and presence of satellites and GPS devices have led to the creation of a huge amounts of spatial and spatio-temporal data, which had significant effects on creating new applications to analyze and mine these data. In this regard, a lot of research has been done on moving objects databases as a part of spatial and spatio-temporal databases. In this dissertation, we focus on those moving objects that are not allowed to move in all directions freely, but they (almost) always are restricted to travel on a specific network. One of the most popular example of these moving objects are vehicles that are supposed to travel on a Road Network. This kind of databases are called Network-constrained (or Fixed-network) Moving Object databases. First, we formalize Network-constrained Moving Object databases, and we come up with a Data Model, Data Schema, and Query Schema. Then, we introduce a data structure to index these kinds of databases. We also present a Traffic Congestion Prediction tool by using Deep Artificial Neural Network. Map Integration, Map Matching, Map Integrity are other applications in this area that we consider in this dissertation.
Notlar:
School code: 2502
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Yer Numarası | Demirbaş Numarası | Shelf Location | Lokasyon / Statüsü / İade Tarihi |
---|---|---|---|
XX(696717.1) | 696717-1001 | Proquest E-Tez Koleksiyonu | Arıyor... |
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