Meng / Li / Xu | Spatial Data and Intelligence | Buch | 978-3-031-32909-8 | sack.de

Buch, Englisch, Band 13887, 272 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 435 g

Reihe: Lecture Notes in Computer Science

Meng / Li / Xu

Spatial Data and Intelligence

4th International Conference, SpatialDI 2023, Nanchang, China, April 13¿15, 2023, Proceedings

Buch, Englisch, Band 13887, 272 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 435 g

Reihe: Lecture Notes in Computer Science

ISBN: 978-3-031-32909-8
Verlag: Springer Nature Switzerland


This book constitutes the refereed proceedings of the 4th International Conference on Spatial Data and Intelligence, SpatialDI 2023, held in Nanchang, China, in April 13–15, 2023.

The 18 full papers included in this book were carefully reviewed and selected from 68 submissions. They were organized in topical sections as follows: traffic management; visualization analysis; spatial big data analysis; spatiotemporal data mining; spatiotemporal data storage; and metaverse.

Meng / Li / Xu Spatial Data and Intelligence jetzt bestellen!

Zielgruppe


Research

Weitere Infos & Material


Traffic Management.- APADGCN: Adaptive Partial Attention Diffusion Graph Convolutional Network for Traffic Flow Forecasting.- DeepParking: Deep Learning-based Planning Method for Autonomous Parking.- Recommendations for Urban Planning based on Non-motorized Travel Data and Street Comfort.- A Composite Grid Clustering Algorithm based on Density and Balance Degree.- Visualization Analysis.- Research on the Visualization Method of Weibo User Sentiment Analysis based on IP Affiliation and Comment Content.- Village Web 3D Visualization System based on Cesium.- Spatial Big Data Analysis.- Spatial-Aware Community Search over Heterogeneous Information Networks.- Ship Classification Based on Trajectories Data and LightGBM Considering Offshore Distance Feature.- CDGCN: An Effective and Efficient Algorithm based on Community Detection for Training Deep and Large Graph Convolutional Networks.- Investigate the Relationship between Traumatic Occurrencesand Socio-economic Status based on Geographic Information System (GIS): The Case of Qingpu in Shanghai, China.- Contact Query Processing based on Spatiotemporal Trajectory.- Influential Community Search over Large Heterogeneous Information Networks.- Spatiotemporal Data Mining.- Fast Mining Prevalent Co-location Patterns over Dense Spatial Datasets.- Continuous Sub-prevalent Co-location Pattern Mining.- The Abnormal Detection Method of Ship Trajectory with Adaptive Transformer Model based on Migration Learning.- Spatiotemporal Data Storage.- A Comparative Study of Row and Column Storage for Time Series Data.- LOACR: A Cache Replacement Method Based on Loop Assist.- Metaverse.- Unifying Reality and Virtuality: Constructing a Cohesive Metaverse Using Complex Numbers.


Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.