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International Conference on Artificial Intelligence and Security

ICAIS 2020: Artificial Intelligence and Security pp 341–352Cite as

An AHP/DEA Methodology for the Public Safety Evaluation

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12240))

Abstract

Public safety may be endangered by events that could lead to huge losses including human life, injuries or property damage, such as crime or disaster. In addition, there are some factors that affect public safety, such as the ratio of temporary residents, per capita GDP, etc. This paper aims at integrating Non-discretionary variable in data envelopment analysis (DEA-NDSC) and analytic hierarchy process (AHP) to evaluate the public safety of cities in China. The proposed AHP/DEA methodology uses the AHP to determine the weights of criteria to assess each item under each criterion, and the DEA-NDSC method to evaluate the efficiency of safety services. A cities’ case of public safety perception is employed to illustrate the proposed method. The results show that the method can effectively and reasonably evaluate the public safety of the city. This research also offers a simple enough and applicable approach to a number of multiple criteria decision making problems.

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Acknowledgements

This work is supported by Guangdong Science and Technology Plan Project (2018KJYZ009), the young teachers training of Guangdong police officer college (2018QNGG06), and Key research platforms and projects of universities in Guangdong province (2018KTSCX157).

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Authors and Affiliations

  1. Guangdong Police College, No. 118, Wenshengzhuang Road, Baiyun District, Guangzhou, China

    Li Mao, Tong Zhang, Wei Du, Han Peng & Lina Zhu

  2. Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, China

    Naqin Zhou

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  1. Li Mao
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  2. Naqin Zhou
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  3. Tong Zhang
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  4. Wei Du
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  5. Han Peng
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  6. Lina Zhu
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Corresponding author

Correspondence to Naqin Zhou .

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Editors and Affiliations

  1. Nanjing University of Information Science, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science, Nanjing, China

    Jinwei Wang

  3. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Mao, L., Zhou, N., Zhang, T., Du, W., Peng, H., Zhu, L. (2020). An AHP/DEA Methodology for the Public Safety Evaluation. In: Sun, X., Wang, J., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2020. Lecture Notes in Computer Science(), vol 12240. Springer, Cham. https://doi.org/10.1007/978-3-030-57881-7_31

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  • DOI: https://doi.org/10.1007/978-3-030-57881-7_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57880-0

  • Online ISBN: 978-3-030-57881-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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