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Download the fantastic book titled Data Driven Intelligent Transportation Systems written by Zhang, Junping, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Data Driven Intelligent Transportation Systems", which was released on 12 February 2014. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Data Driven Intelligent Transportation Systems by Zhang, Junping PDF

The Series in Intelligent Systems publishes titles that cover state of the art knowledge and the latest advances in research and development in intelligent systems. Its scope includes theoretical studies, design methods, and real-world implementations and applications. The Series publishes titles in three core sub-topic areas: Intelligent Automation, Intelligent Transportation Systems, and Intelligent Computing. Titles focus on professional and academic reference works and handbooks. The readership for the series is broad, reflecting the wide range of intelligent systems interest and application, but focuses on engineering (in particular automation, control, mechatronics, robotics, transportation, automotive, aerospace), electronics and electronic design, and computer science. Intelligent Transportation Systems (ITS) are rapidly developing in the world and widely used to optimize the transportation management and plan, enhance city and country security, and improve the traffic users’ travel route, safety and health directly or indirectly. To achieve these goals, a large amount of data are collected from a variety of sources related to ITS. Such abundant and various data lead to a revolution of changing ITS to a more powerful and multifunctional Data-driven ITS. As an associate editor in IEEE transactions on Intelligent Transportation Systems and an associate editor in IEEE Intelligent Systems, Junping Zhang surveys the development of Data-driven ITS in detail, discuss some potential issues closely related to ITS and give a roadmap on the future directions, as well as some recent works on the data-driven ITS. An important contribution in this book is that ITS is closely related to up-to-date data-driven techniques such as data mining, machine learning and computer vision, which are less involved in by other previous ITS-related books. For examples, privacy-preserving and people-centric ITS. The first book for the ITS community that focuses on how to utilize data collected from ITS. Data-driven Intelligent Transportation Systems is a rapidly developing topic. This book is the first dedicated to this important topic. • Introduces the latest approaches and techniques I ITYS, including dimension reduction technique such as nonlinear embedding that can address dimensionality, which often impair the effectiveness of ITS. • Includes a range of real word case studies that show how work in ITS, and related areas including machine learning, vision, and data mining can be applied to transportation systems


Detail About Data Driven Intelligent Transportation Systems PDF

  • Author : Zhang, Junping
  • Publisher : Academic Press
  • Genre : Computers
  • Total Pages : 0 pages
  • ISBN : 9780123983060
  • PDF File Size : 49,8 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Data Driven Intelligent Transportation Systems

Data Driven Intelligent Transportation Systems
  • Publisher : Academic Press
  • File Size : 42,7 Mb
  • Release Date : 12 February 2014
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The Series in Intelligent Systems publishes titles that cover state of the art knowledge and the latest advances in research and development in intelligent systems. Its scope includes theoretical studies,

Data-Driven Solutions to Transportation Problems

Data-Driven Solutions to Transportation Problems
  • Publisher : Elsevier
  • File Size : 46,9 Mb
  • Release Date : 04 December 2018
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Data-Driven Solutions to Transportation Problems explores the fundamental principle of analyzing different types of transportation-related data using methodologies such as the data fusion model, the big data mining approach, computer

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Data-Driven Intelligence in Wireless Networks
  • Publisher : CRC Press
  • File Size : 45,9 Mb
  • Release Date : 27 March 2023
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Covers details on wireless communication problems, conducive for data-driven solutions Provides a comprehensive account of programming languages, tools, techniques, and good practices Provides an introduction to data-driven techniques applied to

Data Analytics for Intelligent Transportation Systems

Data Analytics for Intelligent Transportation Systems
  • Publisher : Elsevier
  • File Size : 39,5 Mb
  • Release Date : 05 April 2017
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Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems that includes detailed coverage of the tools needed to implement these methods using

Mobility Data-Driven Urban Traffic Monitoring

Mobility Data-Driven Urban Traffic Monitoring
  • Publisher : Springer Nature
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  • Release Date : 18 May 2021
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This book introduces the concepts of mobility data and data-driven urban traffic monitoring. A typical framework of mobility data-based urban traffic monitoring is also presented, and it describes the processes

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  • Release Date : 23 October 2020
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Data-Driven Traffic Engineering: Understanding of Traffic and Applications Based on Three-Phase Traffic Theory shifts the current focus from using modeling and simulation data for traffic measurements to the use of

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  • Publisher : World Scientific
  • File Size : 23,6 Mb
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This book is designed as a popular science book on big data analytics in intelligent transportation systems. It aims to provide an introduction to big-data transportation starting from an overview

Handbook of Mobility Data Mining, Volume 3

Handbook of Mobility Data Mining, Volume 3
  • Publisher : Elsevier
  • File Size : 55,5 Mb
  • Release Date : 29 January 2023
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Handbook of Mobility Data Mining: Volume Three: Mobility Data-Driven Applications introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand