Using Variable Fuzzy Set Theory and Information Entropy for Air Pollution Risk Assessment in Beijing, China | Zendy

Liyun Yang | Zendy; Songtao Wu | Zendy

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Using Variable Fuzzy Set Theory and Information Entropy for Air Pollution Risk Assessment in Beijing, China

Author(s) -

Liyun Yang,

Songtao Wu

Publication year - 2011

Publication title -

energy procedia

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.474

H-Index - 81

ISSN - 1876-6102

DOI - 10.1016/j.egypro.2011.10.557

Subject(s) - beijing , china , entropy (arrow of time) , fuzzy logic , fuzzy set , environmental science , air pollution , variable (mathematics) , pollution , data mining , mathematics , computer science , geography , artificial intelligence , physics , mathematical analysis , thermodynamics , chemistry , archaeology , organic chemistry , ecology , biology

Considering that the air pollution risk assessment is a variable fuzzy concept with multiple indicators and classes and there is the limit for the weight value of variable fuzzy evaluation method, the variable fuzzy mathematics method and the information entropy are combined to evaluate the air pollution risk of different seasons in sixteen districts of Beijing in 2009. The multi-objective group decision-making problem under air pollution risk has been solved by variable fuzzy method and the weight problem has been modified by information entropy, which makes the evaluating results more objective. From quantitative assessment, the air pollution risk of winter season in south seven districts of Beijing was on the margin in 2009. Beijing needs to optimize energy structure by introducing and developing the use of cleaner high-quality energy to decrease air pollution risk grade on winter. Keywords-air pollution risk assessment; variable fuzzy set theory; information entropy; Beijing

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