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A New Method for Comprehensive Evaluation of Air Quality in Urban Agglomeration

机译:一种全新评价城市集群空气质量的新方法

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In this study, a new method for a comprehensive evaluation of air quality in urban agglomerations was developed based on a prototype used to solve the spatial Steiner-Weber point. With this method, the air quality information of each city in the city group is aggregated into an optimal gathering point, and then the air quality of the city group is then dynamically evaluated each year. According to the relevant data of the China Statistical Yearbook 2018, we applied this method to aggregate the air quality indices of the major cities in the Beijing-Tianjin-Hebei urban agglomeration from 2014 to 2017. Using the plant growth simulation algorithm (PGSA), the optimal assembly points were calculated to be of a higher accuracy, compared to the traditional mean value aggregation method. Finally, the air quality of the Beijing-Tianjin-Hebei urban agglomeration during each year was evaluated dynamically based on the obtained assembly points. The results show that the air quality of the urban agglomeration is ranked as follows: Y2016 Y2015 Y2017 Y2014.
机译:在这项研究中,基于用于解决空间施泰纳 - 韦伯点的原型开发了一种全面评估城市集群空气质量的新方法。通过这种方法,城市集团中每个城市的空气质量信息被聚集成最佳聚焦点,然后每年动态地评估城市组的空气质量。根据中国统计年鉴的相关数据2018年,我们将这种方法汇总了2014年至2017年京津 - 河北省城市集聚的主要城市的空气质量指标。使用植物生长仿真算法(PGSA),与传统平均值聚集方法相比,计算最佳组装点以具有更高的精度。最后,根据所获得的装配要点,每年进行一次北京 - 天津 - 河北城市群的空气质量。结果表明,城市集聚的空气质量排名如下:Y2016 Y2015 Y2017 Y2014。

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