research-article

On Two-Dimensional Structural Information of Beijing Transportation Networks Based on Traffic Big Data

Authors:

Zundong ZhangAuthors Info & Claims

ICCBDC '18: Proceedings of the 2018 2nd International Conference on Cloud and Big Data Computing

Pages 28 - 32

https://doi.org/10.1145/3264560.3264564

Published: 03 August 2018 Publication History

Abstract

Hierarchy is a fundamental characteristic of many complex systems. The methods of structural information have been taken as a prospective way for quantifying dynamical network complexity. This paper is based on the study of the high-dimensional natural structural information entropy in networks. And then we propose a new similarity District Structural Information (DSI) index, which takes the characteristics of network districts into consideration, to analyze the complexity of dynamical network districts. Based on the method, this paper applies the district structural information to explain the equilibrium problem in real-world networks. And taking Beijing traffic network and its districts to complete experiments demonstrates that the DSI index can reflect the equilibrium of the network and the districts effectively.

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Cited By

Wang ZZhang MChu RZhao L(2020)Modeling and Planning Multimodal Transport Paths for Risk and Energy Efficiency Using AND/OR Graphs and Discrete Ant Colony OptimizationIEEE Access10.1109/ACCESS.2020.30103768(132642-132654)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3010376

Index Terms

On Two-Dimensional Structural Information of Beijing Transportation Networks Based on Traffic Big Data
1. Networks
  1. Network performance evaluation
    1. Network experimentation

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ICCBDC '18: Proceedings of the 2018 2nd International Conference on Cloud and Big Data Computing

August 2018

98 pages

ISBN:9781450364744

DOI:10.1145/3264560

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Brookes: Oxford Brookes University
Northumbria University: University of Northumbria at Newcastle

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Association for Computing Machinery

New York, NY, United States

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Published: 03 August 2018

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ICCBDC'18: 2018 2nd International Conference on Cloud and Big Data Computing

August 3 - 5, 2018

Barcelona, Spain

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Cited By

Wang ZZhang MChu RZhao L(2020)Modeling and Planning Multimodal Transport Paths for Risk and Energy Efficiency Using AND/OR Graphs and Discrete Ant Colony OptimizationIEEE Access10.1109/ACCESS.2020.30103768(132642-132654)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3010376

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