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The Study on Evaluation Method of Urban Network Security in the Big Data Era

Qingyuan Zhoua, Jianjian Luob

a Department of Economics and Management, Changzhou Administrative College, Changzhou, 213001, China;
b Department of Information Management, Changzhou College of Information Technology, Changzhou, 213001, China

* Corresponding Author: Qingyuan Zhou, email

Intelligent Automation & Soft Computing 2018, 24(1), 133-138. https://doi.org/10.1080/10798587.2016.1267444

Abstract

Big data is an emerging paradigm applied to datasets whose size is beyond the ability of commonly used software tools to capture, manage, and process the data within a tolerable elapsed time. In a Smarter City, available resources are harnessed safely, sustainably and efficiently to achieve positive, measurable economic and societal outcomes. Most of the challenges of Big Data in Smart Cities are multi-dimensional and can be addressed from different multidisciplinary perspectives. Based on the above considerations, this paper combined the PSR method, the fuzzy logic model and the entropy weight method in an empirical study for feasible urban public security evaluation modeling. The PSR method was used to establish an evaluation index system regarding the essence of public security. The Entropy method was used in the weighing assignment process to verify the objectivity of this modeling. The fuzzy method was used for the quantitative analysis to determine the fuzziness of urban public security.

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Cite This Article

APA Style
Zhou, Q., Luo, J. (2018). The study on evaluation method of urban network security in the big data era. Intelligent Automation & Soft Computing, 24(1), 133-138. https://doi.org/10.1080/10798587.2016.1267444
Vancouver Style
Zhou Q, Luo J. The study on evaluation method of urban network security in the big data era. Intell Automat Soft Comput . 2018;24(1):133-138 https://doi.org/10.1080/10798587.2016.1267444
IEEE Style
Q. Zhou and J. Luo, “The Study on Evaluation Method of Urban Network Security in the Big Data Era,” Intell. Automat. Soft Comput. , vol. 24, no. 1, pp. 133-138, 2018. https://doi.org/10.1080/10798587.2016.1267444



cc Copyright © 2018 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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