Fuzzy Correlation Evaluation of Forest Ecological Carrying Capacity Considering the Interaction between Attributes
Jian Lin 1,2
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College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, Fujian, 350002, China
Business School, Sichuan University, Chengdu, Sichuan, 610064, China
College of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou, Fujian, 350002, China
Submission date: 2022-11-03
Final revision date: 2023-01-02
Acceptance date: 2023-02-02
Online publication date: 2023-03-17
Publication date: 2023-05-18
Corresponding author
Jian Lin   

Fujian Agriculture and Forestry University, China
Pol. J. Environ. Stud. 2023;32(3):2733-2747
Forest ecological carrying capacity can measure the balance between environmental pollution and forest ecosystems in the process of social development. This paper first selects 17-year panel data of five provinces in southeastern China, and uses the generalized trapezoidal fuzzy number to describe and express them based on the flat peak characteristic of the data itself; Secondly, the generalized Shapley value with the introduction of λ-fuzzy measure is used to measure the correlation between attribute indicators, and the indicator weight is determined by the attributes contribution; Then, an optimal fuzzy measure linear programming model is established based on the similarity, which is used to determine the generalized Shapley value of each attribute indicator. Finally, the λ-Shapley-Choquet integral operator is used for information aggregation and the centroid method is used to rank the comprehensive evaluation values. The results show that the forest ecological carrying capacity of five provinces during 2004-2020 is ranked from high to low as Fujian Province, Jiangxi Province, Zhejiang Province, Guangxi Province, and Guangdong Province. Based on this, it is proposed that strengthening the forest’s ecological carrying capacity in southeastern China should be carried out in parallel from two aspects: enriching forest resources and reducing environmental pollution.
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