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Titlebook: Geoinformatics for Intelligent Transportation; Igor Ivan,Itzhak Benenson,Tomáš Inspektor Book 2015 Springer International Publishing Switz

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书目名称Geoinformatics for Intelligent Transportation
编辑Igor Ivan,Itzhak Benenson,Tomáš Inspektor
视频videohttp://file.papertrans.cn/384/383285/383285.mp4
概述Presents the latest research achievements in the area of geoinformatics and transportation.Multidisciplinary focus.Combination of theoretical papers and applications.Includes supplementary material:
丛书名称Lecture Notes in Geoinformation and Cartography
图书封面Titlebook: Geoinformatics for Intelligent Transportation;  Igor Ivan,Itzhak Benenson,Tomáš Inspektor Book 2015 Springer International Publishing Switz
描述The aim of the book is to present and discuss new methods, issues and challenges involved in geoinformatics’ contribution to making transportation more intelligent, efficient and human-friendly. It covers a wide range of topics related to transportation and geoinformatics. The themes are divided into four main sections: Transport modeling, Sensor data and services, Intelligent transport systems, and Transport planning and accessibility.
出版日期Book 2015
关键词Autonomous Vehicle Systems; Geoinformatics; Intelligent Transport System; Public Transit Advances; Traff
版次1
doihttps://doi.org/10.1007/978-3-319-11463-7
isbn_softcover978-3-319-36445-2
isbn_ebook978-3-319-11463-7Series ISSN 1863-2246 Series E-ISSN 1863-2351
issn_series 1863-2246
copyrightSpringer International Publishing Switzerland 2015
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Optimal Placement of the Bike Rental Stations and Their Capacities in Olomouc,ension Network Analyst for ArcGIS was used for location and allocation analyses. Moreover, the suggestion of capacities (number of position for bikes) for each station was calculated. The result is two variants for 3 and 4 min walking time to the rental station.
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Die emotionale Erfahrung des Asylse Eindhoven region, The Netherlands, is used to examine the performance of this algorithm. Results based on a small sample show that the algorithm has a good performance in both processing efficiency and prediction accuracy of correctly identified instances. Prediction accuracy using a small sample is 87.02 %.
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Detecting Spatial and Temporal Route Information of GPS Traces,e Eindhoven region, The Netherlands, is used to examine the performance of this algorithm. Results based on a small sample show that the algorithm has a good performance in both processing efficiency and prediction accuracy of correctly identified instances. Prediction accuracy using a small sample is 87.02 %.
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