Last edited by Kigahn
Monday, July 20, 2020 | History

1 edition of Spatio-temporal Networks found in the catalog.

Spatio-temporal Networks

Modeling and Algorithms

by Betsy George

  • 371 Want to read
  • 28 Currently reading

Published by Springer New York, Imprint: Springer in New York, NY .
Written in English

    Subjects:
  • Database management,
  • Graph theory,
  • Computer science,
  • Geographic information systems,
  • Geographical Information Systems/Cartography

  • Edition Notes

    Statementby Betsy George, Sangho Kim
    SeriesSpringerBriefs in Computer Science
    ContributionsKim, Sangho, SpringerLink (Online service)
    Classifications
    LC ClassificationsQA76.9.D3
    The Physical Object
    Format[electronic resource] :
    ID Numbers
    Open LibraryOL27088617M
    ISBN 109781461449188

    Spatio-temporal networks (STN)are spatial networks whose topology and/or attributes change with time. Designing a STN database would require the development of data models, query languages, and indexing methods to efficiently represent, query, store, and manage time-variant properties of the network. Winner of the DeGroot Prize. A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methods Noel Cressie and Christopher K. Wikle, are also winners of the PROSE Award in the Mathematics category, for the book “Statistics for Spatio-Temporal Data” (), published by.

      Spatio-Temporal Congestion Patterns in Urban Traffic Networks F. Rempe et al. One possibility to quantify the ability of a set of clusters ܥଵሬሬሬሬԦǡ Ç¥ Ç¡ ܥ௡௖ሬሬሬሬሬሬԦ to represent the traffic situation of the entire network is . Book January In a spatio-temporal network, this computation assumes added semantics due to the dependence of network attributes on time. Shortest paths can be computed either for a.

      That work led naturally into spatio-temporal epidemiology, which remains an area of interest. He has published about refereed articles and a book on modeling environmental processes. His contributions to statistics have been recognized by a number of s: 2. This website, , is meant to serve several purposes: It is a landing page for our book Spatio-Temporal Statistics with R (including an associated R package STRbook, reviews, and an errata sheet); it offers an opportunity for individuals to participate in a Discussion Forum; and it is a place where new software, data sets, and articles on spatio-temporal statistics can.


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Spatio-temporal Networks by Betsy George Download PDF EPUB FB2

“This monograph discusses spatio-temporal networks (STNs). The book is extremely focused and well-written. manuscript should be accessible to a number of interested researchers and not just the practitioners in the field of spatial databases and STNs.

Cited by:   Overview Spatio-temporal networks (STN)are spatial networks whose topology and/or attributes change with time.

These are encountered in many critical areas of everyday life such as transportation networks, electric power distribution grids, and social networks of mobile eling and computations raise significant : Betsy George. Spatio-temporal networks (STN)are spatial networks whose topology and/or attributes change with time.

These are encountered in many critical areas of everyday life such as transportation networks, electric power distribution grids, and social networks of mobile users. STN modeling and computations raise significant challenges. Spatio-temporal networks are spatial networks whose topology and parameters change with time.

Introduction Spatio-temporal networks (STN)are spatial networks whose topology and/or attributes change with time. These are encountered in many critical areas of everyday life such as transportation networks, electric power distribution grids, and social networks of mobile users.

STN modeling and computations raise significant challenges. THE RAPID GROWTH IN SIZE, VARIETY AND UPDATE RATE OF SPATIO-TEMPORAL DATA IS CREATING NEW CHALLENGES AND OPPORTUNITIES TO EFFICIENTLY STORE, VALIDATE, PROCESS AND ANALYZE SPATIO-TEMPORAL NETWORKS WITH LARGE TIME-SERIES DATA.

THIS PAPER DESCRIBES THE CHALLENGES AND TRENDS IN BIG DATA ANALYTICS FOR SPATIO-TEMPORAL NETWORKS. This chapter provides brief descriptions of key real world domains where spatio-temporal networks play a significant role such as multimodal transportation networks and sensor networks.

The chapter illustrates the modeling of multimodal transportation networks and sensor networks using time aggregated graphs. Spatio-temporal networks represent networks where entities have spatial attributes and the topology and parameters display time-dependence.

Spatio-temporal networks for speech and visual pattern recognition I am interested in the representational, computational, and adaptive properties of spatio-temporal networks and the use of such nets in speech and visual pattern recogntion.

A spatio-temporal neural net differs from other neural networks in two ways. The analysis of a network's spatio-temporal structure (defined in §2) provides the foundation to measure its topological, temporal and spatial function.

These measures are presented in §3, along with systematic attack strategies designed to expose different weaknesses in the network. Given a spatial network and its variations over time (e.g., time-varying travel times on road networks) this chapter discusses how to model, query and store spatio-temporal networks.

This book explores new methods and techniques for research about merchant networks and maritime routes of trade during the First Global Age through the use of Geographic Information Systems (GIS) as a tool to visualize the formation of trading systems, database management, cartography and spatio-temporal analysis in Historical GIS.

Spatio-temporal Design presents a comprehensive state-of-the-art presentation combining both classical and modern treatments of network design and planning for spatial and spatio-temporal data acquisition.

A common problem set is interwoven throughout the chapters, providing various perspectives to illustrate a complete insight to the problem. The construction of spatio-temporal networks is very sensitive to geolocation and temporal inconsistencies driving to incorrect phenomena representation and therefore incorrect interpretation caused by to spurious networks generated from this data (e.g, a network constructed over inconsistent spatial data over the time, may lead the generation of networks components and measures that do not.

Geocomputational methods, including agent-based modelling, artifical neural networks and evolutionary computing Big Data - lessons for researchers "Written in an engaging and accessible manner, this book does a marvelous job of balancing its coverage on principles.

Spatiotemporal Network Analysis and Visualization: /ch Spatiotemporal social network analysis shows relationships among people at a particular time and location. This paper presents an algorithm that mines textCited by: 5.

Spatio Temporal Narratives Download Spatio Temporal Narratives books, This book explores new methods and techniques for research about merchant networks and maritime routes of trade during the First Global Age through the use of Geographic Information Systems (GIS) as a tool to visualize the formation of trading systems, database management.

Spatio-temporal networks (STN)are spatial networks whose topology and/or attributes change with time. These are encountered in many critical. Deep spatio-temporal residual neural networks for road-network-based data modeling.

International Journal of Geographical Information Science: Vol. 33, No. 9, pp. Given a spatial network and its variations over time (e.g., time-varying travel times on road networks) this chapter discusses how to model, query and store spatio-temporal networks.

This problem has application in several domains such as transportation networks, emergency planning, knowledge discovery from sensor data, and crime analysis.

Spatio-temporal Analysis of Extreme Hydrological Events offers an extensive view of the experiences and applications of the latest developments and methodologies for analyzing and understanding extreme environmental and hydrological events.

The book addresses the topic using spatio-temporal methods, such as space-time geostatistics, machine learning, statistical theory, hydrological modelling.

Book Description. Teaches Students How to Perform Spatio-Temporal Analyses within Epidemiological Studies. Spatio-Temporal Methods in Environmental Epidemiology is the first book of its kind to specifically address the interface between environmental epidemiology and spatio-temporal modeling.

In response to the growing need for collaboration between statisticians and environmental.Spatio-Temporal Dynamics of Landscape Connectivity and Ecological Network Construction in Long Yangxia Basin at the Upper Yellow River by Fangning Shi, Shiliang Liu *, Yi An, Yongxiu Sun, Shuang Zhao, Yixuan Liu and Mingqi Li.