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On Consistency Test Method of Expert Opinion in Ecological Security Assessment

Author

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  • Zaiwu Gong

    (Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, College of Economics and Management, Nanjing University of Information Science and Technology, Nanjing 210044, China)

  • Lihong Wang

    (Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, College of Economics and Management, Nanjing University of Information Science and Technology, Nanjing 210044, China)

Abstract

To reflect the initiative design and initiative of human security management and safety warning, ecological safety assessment is of great value. In the comprehensive evaluation of regional ecological security with the participation of experts, the expert’s individual judgment level, ability and the consistency of the expert’s overall opinion will have a very important influence on the evaluation result. This paper studies the consistency measure and consensus measure based on the multiplicative and additive consistency property of fuzzy preference relation (FPR). We firstly propose the optimization methods to obtain the optimal multiplicative consistent and additively consistent FPRs of individual and group judgments, respectively. Then, we put forward a consistency measure by computing the distance between the original individual judgment and the optimal individual estimation, along with a consensus measure by computing the distance between the original collective judgment and the optimal collective estimation. In the end, we make a case study on ecological security for five cities. Result shows that the optimal FPRs are helpful in measuring the consistency degree of individual judgment and the consensus degree of collective judgment.

Suggested Citation

  • Zaiwu Gong & Lihong Wang, 2017. "On Consistency Test Method of Expert Opinion in Ecological Security Assessment," IJERPH, MDPI, vol. 14(9), pages 1-18, September.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:9:p:1012-:d:110825
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    References listed on IDEAS

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    1. Dong, Yucheng & Xu, Yinfeng & Li, Hongyi, 2008. "On consistency measures of linguistic preference relations," European Journal of Operational Research, Elsevier, vol. 189(2), pages 430-444, September.
    2. Lafuite, A.-S. & Loreau, M., 2017. "Time-delayed biodiversity feedbacks and the sustainability of social-ecological systems," Ecological Modelling, Elsevier, vol. 351(C), pages 96-108.
    3. Herrera-Viedma, E. & Herrera, F. & Chiclana, F. & Luque, M., 2004. "Some issues on consistency of fuzzy preference relations," European Journal of Operational Research, Elsevier, vol. 154(1), pages 98-109, April.
    4. Gong, Zaiwu & Xu, Xiaoxia & Zhang, Huanhuan & Aytun Ozturk, U. & Herrera-Viedma, Enrique & Xu, Chao, 2015. "The consensus models with interval preference opinions and their economic interpretation," Omega, Elsevier, vol. 55(C), pages 81-90.
    5. Gong, Zaiwu & Zhang, Huanhuan & Forrest, Jeffrey & Li, Lianshui & Xu, Xiaoxia, 2015. "Two consensus models based on the minimum cost and maximum return regarding either all individuals or one individual," European Journal of Operational Research, Elsevier, vol. 240(1), pages 183-192.
    6. Xiao Tan & Zaiwu Gong & Minji Huang & Zhou-Jing Wang, 2017. "Selecting Cooking Methods to Decrease Persistent Organic Pollutant Concentrations in Food of Animal Origin Using a Consensus Decision-Making Model," IJERPH, MDPI, vol. 14(2), pages 1-18, February.
    7. Guangquan Zhang & Jie Lu, 2003. "An Integrated Group Decision-Making Method Dealing with Fuzzy Preferences for Alternatives and Individual Judgments for Selection Criteria," Group Decision and Negotiation, Springer, vol. 12(6), pages 501-515, November.
    8. Xiayu Tong & Zhou-Jing Wang, 2016. "A Group Decision Framework with Intuitionistic Preference Relations and Its Application to Low Carbon Supplier Selection," IJERPH, MDPI, vol. 13(9), pages 1-16, September.
    9. Wuyong Qian & Zhou-Jing Wang & Kevin W. Li, 2016. "Medical Waste Disposal Method Selection Based on a Hierarchical Decision Model with Intuitionistic Fuzzy Relations," IJERPH, MDPI, vol. 13(9), pages 1-13, September.
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    Cited by:

    1. Ning Zhang & Zaiwu Gong & Kedong Yin & Yuhong Wang, 2018. "Special Issue “Decision Models in Green Growth and Sustainable Development”," IJERPH, MDPI, vol. 15(6), pages 1-8, May.
    2. Xi Chen & Dawei Xu & Safa Fadelelseed & Lianying Li, 2019. "Spatiotemporal Analysis and Control of Landscape Eco-Security at the Urban Fringe in Shrinking Resource Cities: A Case Study in Daqing, China," IJERPH, MDPI, vol. 16(23), pages 1-26, November.

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