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Stepwise genetic algorithm for adaptive management: Application to air quality monitoring network optimization

文献类型： 外文期刊

作者： Li, Jierui 1 ; Zhang, Hanyue 1 ; Luo, Yuzhou 3 ; Deng, Xunfei 4 ; Grieneisen, Michael L. 3 ; Yang, Fumo 1 ; Di, Baofen 1 ;

作者机构： 1.Sichuan Univ, Dept Environm Sci & Engn, Chengdu 610065, Sichuan, Peoples R China

2.Sichuan Univ, Inst Disaster Management & Reconstruct, Chengdu 610200, Sichuan, Peoples R China

3.Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA

4.Zhejiang Acad Agr Sci, Inst Digital Agr, Hangzhou 310021, Zhejiang, Peoples R China

5.Natl Engn Res Ctr Flue Gas Desulfurizat, Chengdu 610065, Sichuan, Peoples R China

6.Sichuan Univ, Med Big Data Ctr, Chengdu 610041, Sichuan, Peoples R China

7.Sichuan Univ, Sino German Ctr Water & Hlth Res, Chengdu 610065, Sichuan, Peoples R China

关键词： Air quality monitoring network; Stepwise optimization; Prediction variance; Kriging; Genetic algorithm

期刊名称：ATMOSPHERIC ENVIRONMENT （ 影响因子：4.798； 五年影响因子：5.295 ）

ISSN： 1352-2310

年卷期： 2019 年 215 卷

页码：

收录情况： SCI

摘要： A novel algorithm named the stepwise genetic algorithm (SGA) is proposed to optimize the air quality monitoring network of mainland China under the framework of adaptive management. SGA is adapted from the genetic algorithm by modifying the operators of "mutation" and "crossover" to increase the number of removed sites by one at each step. Approximately half of the sites are adequate to achieve the same mean kriging variance (MKV) as that from all the sites, and the PM2.5 maps interpolated from these two site sets are very similar. Based on the site array proposed by SGA, the MKV shows a U-shaped trend with the number of removed sites, where the initial decrease of MKV (indicating improvement of interpolation accuracy by removing some sites) has only rarely been reported before. Mathematical proof demonstrates that the clustered sites tend to cause collinearity in the covariance matrix and hence result in MKV inflation.

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