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基于FA-SVM优化LUR模型的汾渭平原PM2.5时空格局模拟

张平 张凤倩 朱慧敏 李明垚 黄翰林

西安工程大学学报2025,Vol.39Issue(3):89-101,13.
西安工程大学学报2025,Vol.39Issue(3):89-101,13.DOI:10.13338/j.issn.1674-649x.2025.03.011

基于FA-SVM优化LUR模型的汾渭平原PM2.5时空格局模拟

Simulation of spatiotemporal patterns of PM2.5 in the Fenwei Plain based on FA-SVM optimized LUR model

张平 1张凤倩 2朱慧敏 2李明垚 2黄翰林2

作者信息

  • 1. 西安工程大学 环境与化学工程学院,陕西 西安 710048||西安建筑科技大学 西部绿色建筑国家重点实验室,陕西 西安 710055||长安大学 西安市国土空间信息重点实验室,陕西 西安 710075
  • 2. 西安工程大学 环境与化学工程学院,陕西 西安 710048
  • 折叠

摘要

Abstract

To accurately capture the complex relationship between PM2.5 and predictive factors,and to obtain spatially continuous PM2.5 pollution distribution with higher resolution and predic-tion accuracy,a regional PM2.5 pollution early warning mechanism is constructed.In this study,the firefly algorithm-support vector machine(FA-SVM)is used to optimize the land use regres-sion(LUR)model,estimating the PM2.5 mass concentrations in the Fenwei Plain in 2019 at a spa-tial resolution of 1 km.The results indicate that,compared to conventional LUR and SVM mod-els,FA-SVM demonstrates superior predictive performance.The ten-fold cross-validation coeffi-cient of determination for FA-SVM is as high as 0.90,with a root mean square error and mean absolute error of 12.29 μg/m3 and 8.99 μg/m3,respectively.In contrast,the validation coefficient of determination for LUR and SVM are 0.75 and 0.85,respectively,with root mean square error values of 19.57 μg/m3 and 14.37 μg/m3,and mean absolute error values of 14.84 μg/m3 and 9.62 μg/m3,respectively.PM2.5 pollution in the Fenwei Plain in 2019 exhibits significant spatio-temporal heterogeneity.Temporally,PM2.5 pollution is most severe in winter,gradually decrea-sing in spring,autumn,and summer.Spatially,areas with relatively higher economic levels show higher PM2.5 mass concentration,forming high-value aggregation zones,while the Qinling Mountains region represents low-value aggregation zones.Overall,PM2.5 exhibits a spatial pattern of higher concentrations in the central region and lower concentrations in the surrounding areas.

关键词

土地利用回归/萤火虫算法-支持向量机/PM2.5时空特征/模型优化/汾渭平原

Key words

land use regression(LUR)/firefly algorithm-support vector machine(FA-SVM)/spatiotemporal characteristics of PM2.5/model optimization/the Fenwei Plain

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资源环境

引用本文复制引用

张平,张凤倩,朱慧敏,李明垚,黄翰林..基于FA-SVM优化LUR模型的汾渭平原PM2.5时空格局模拟[J].西安工程大学学报,2025,39(3):89-101,13.

基金项目

陕西省自然科学基础研究计划项目(2021JM-447) (2021JM-447)

西部绿色建筑国家重点实验室开放基金项目(LSKF202309) (LSKF202309)

西安市国土空间信息重点实验室(长安大学)开放基金项目(300102353507) (长安大学)

西安工程大学学报

1674-649X

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