高级搜索

基于元胞自动机的大气扩散模型及GIS可视化

,  ,  ,  ,  ,  ,  , 

downloadPDF

上一篇

下一篇

韦宗明, 艾矫燕, 李修华, 邓超冰, 吴宗书, 蔡亚娟, 吴思知, 徐海扬. 基于元胞自动机的大气扩散模型及GIS可视化[J]. 环境工程学报, 2016, 10(5): 2527-2534. doi: 10.12030/j.cjee.201412091
引用本文: 韦宗明, 艾矫燕, 李修华, 邓超冰, 吴宗书, 蔡亚娟, 吴思知, 徐海扬. 基于元胞自动机的大气扩散模型及GIS可视化[J]. 环境工程学报, 2016, 10(5): 2527-2534. doi: 10.12030/j.cjee.201412091
shu
Wei Zongming, Ai Jiaoyan, Li Xiuhua, Deng Chaobing, Wu Zongshu, Cai Yajuan, Wu Sizhi, Xu Haiyang. Air diffusion model and GIS visualization based on cellular automata[J]. Chinese Journal of Environmental Engineering, 2016, 10(5): 2527-2534. doi: 10.12030/j.cjee.201412091
Citation: Wei Zongming, Ai Jiaoyan, Li Xiuhua, Deng Chaobing, Wu Zongshu, Cai Yajuan, Wu Sizhi, Xu Haiyang. Air diffusion model and GIS visualization based on cellular automata[J]. Chinese Journal of Environmental Engineering, 2016, 10(5): 2527-2534. doi: 10.12030/j.cjee.201412091
shu

基于元胞自动机的大气扩散模型及GIS可视化

  • 1.

    广西大学电气工程学院, 南宁 530004

  • 2.

    广西环境监测中心站, 南宁 530000

  • 基金项目:

    广西科技计划自治区主席科技资金(1517-08)

    广西自然科学基金重大项目(2013GXNSFEA053001)

  • 中图分类号: X701

Air diffusion model and GIS visualization based on cellular automata

  • 1.

    College of Electrical Engineering, Guangxi University, Nanning 530004, China

  • 2.

    Guangxi Autonomous Region Environmental Monitoring Central Station, Nanning 530000, China

  • Fund Project:

HTML全文

  • 摘要: 基于对目前常用大气扩散模型以及大气扩散特性的分析,采用通过局部转移规则实现宏观涌现的复杂系统建模工具-元胞自动机来建立时空动态的大气扩散模型。结合MATLAB的矩阵运算能力和GIS的栅格数据处理能力进行模型的实现与可视化。仿真结果表明,所建立的模型不仅能动态模拟大气污染的高斯扩散等常用扩散模式,通过合理的模型参数设定也可动态模拟非常规扩散模式,如模拟时段内风向风速发生多次变化或者模拟区域存在湍流等条件下的扩散过程,得到准确的污染物时空动态分布,可望为大气污染防治提供决策支持。
    Abstract: Based on the analysis of common models and features of air diffusion, a spatial-temporal dynamic model was built with cellular automata, which is an efficiently complex system modeling method to achieve macro-emergence under local-transition rules. The model was established and visualized through matrix computing and raster data processing in MATLAB and GIS software, respectively. Simulation results revealed that the model could be applied in simulating the regular dynamical diffusion patterns, such as Gaussian diffusion. Moreover, simulation of unconventional dynamical diffusion patterns could also be efficient if accompanied by reasonable parameters, for instance simulation of the air diffusion progress under conditions of an unstable wind direction and speed during the simulation period or even a turbulent flow appearing in the simulation area. The model was expected to estimate an accurate spatial-temporal dynamic distribution of air pollutants, which could be used for pollution control decision-making purposes.
  • [1] 平措. 大气污染扩散长期模型的应用研究. 天津: 天津大学硕士学位论文, 2006 Ping Cuo. Application of atmospheric pollutant long-term diffusion model. Tianjin: Master Dissertation of Tianjin University, 2006(in Chinese)
    [2] 向敏, 韩永翔, 邓祖琴. 2007年我国城市大气污染时空分布特征. 环境监测管理与技术, 2009, 21(3): 33-36 Xiang Min, Han Yongxiang, Deng Zuqin. Spatial-temporal distribution characteristic of Chinese cities air pollution in 2007. The Administration and Technique of Environmental Monitoring, 2009, 21(3): 33-36(in Chinese)
    [3] 张斌才, 赵军. 大气污染扩散的高斯烟羽模型及其GIS集成研究. 环境监测管理与技术, 2008, 20(5): 17-19 Zhang Bincai, Zhao Jun. Application of caussian plume model of atmosphere diffusion integrated with GIS. The Administration and Technique of Environmental Monitoring, 2008, 20(5): 17-19(in Chinese)
    [4] 黄金杰, 杨桂花, 马骏驰. 基于高斯的大气污染评价模型. 计算机仿真, 2011, 28(2): 101-104 Huang Jinjie, Yang Guihua, Ma Junchi. Evaluation model of air pollution based on Gauss mode. Computer Simulation, 2011, 28(2): 101-104(in Chinese)
    [5] 段晓东, 王存睿, 刘向东. 元胞自动机理论研究及其仿真应用. 北京: 科学出版社, 2012
    [6] González R. E. R., de Figueirêdo P. H., Coutinho S. Cellular automata approach for the dynamics of HIV infection under antiretroviral therapies: The role of the virus diffusion. Physica A: Statistical Mechanics and its Applications, 2012, 392(19): 4717-4725
    [7] Karafyllidis L. A model for the prediction of oil slick movement and spreading using cellular automata. Environment International, 1997, 23(6): 839-850
    [8] Yang Qingsheng, Li Xia, Shi Xun. Cellular automata for simulating land use changes based on support vector machines. Computers & Geosciences, 2008, 34(6): 592-602
    [9] Chopard B., Droz M. 物理系统的元胞自动机模拟. 祝玉学, 赵学龙, 译. 北京: 清华大学出版社, 2003
    [10] Wolfram S. A New Kind of Science. Michigan: Wolfram Media, 2002
    [11] Alexandridis A., Vakalis D., Siettos C. I., et al. A cellular automata model for forest fire spread prediction: The case of the wildfire that swept through Spetses Island in 1990. Applied Mathematics and Computation, 2008, 204(1): 191-201
    [12] Ganguly N. Cellular automata evolution: Theory and applications in pattern recognition and classification. India: Doctor Dissertation of CST Dept. BECDU, 2003
    [13] Sarkar P. A brief history of cellular automata. ACM Computing Systems, 2000, 32(1): 80-107
    [14] Chopard B, Droz M. Cellular Automata Modeling of Physical Systems. Cambridge: Cambridge University Press, 1998
    [15] Chaudhuri P. P., Chowdhury D. R., Nandi S., et al. Additive Cellular Automata-Theory and Applications. California, USA: IEEE Computer Society Press, 1997
    [16] Ermentrout G. B., Edelstein-Keshet L. Cellular automata approaches to biological modeling. Journal of Theoretical Biology, 1993, 160(1): 97-133
    [17] Wolfram S. Cellular Automata and Complexity. Boulder, Colorado: Westview Press, 1994
    [18] Wolfram S. Cellular automata as models of complexity. Nature, 1984, 311(5985): 419-424
    [19] Wolfram S. Universality and complexity in cellular automata. Physica D: Nonlinear Phenomena, 1984, 10(1-2): 1-35
    [20] Langton C. G. Self-reproduction in cellular automata. Physica D: Nonlinear Phenomena, 1984, 10(1-2): 134-144
    [21] Li Wentian, Packard N. H., Langton C. G. Transition phenomena in cellular automata rule space. Physica D: Nonlinear Phenomena, 1990, 45(1-3): 77-94
    [22] Li Wentian, Packard N. H. The structure of the elementary cellular automata rule space. Complex Systems, 1990, 4(3): 281-297
    [23] 周成虎, 孙占利, 谢一春. 地理元胞自动机研究. 北京: 科学出版社, 1999
    [24] 李才伟. 元胞自动机及复杂系统的时空演化模拟. 武汉: 华中科技大学博士学位论文, 1997 Li Caiwei. Cellular automata and simulating to the spatiotemporal evolution of complex system. Wuhan: Doctor Dissertation of Huazhong University of Science and Technology, 1997(in Chinese)
    [25] 王中鲜, 赵魁, 徐建东. MATLAB建模与仿真应用教程. 北京: 机械工业出版社, 2014
  • 加载中
WeChat 点击查看大图
计量
  • 文章访问数:  2261
  • HTML全文浏览数:  1864
  • PDF下载数:  403
  • 施引文献:  0
出版历程
  • 收稿日期:  2015-09-03
  • 刊出日期:  2016-06-03
韦宗明, 艾矫燕, 李修华, 邓超冰, 吴宗书, 蔡亚娟, 吴思知, 徐海扬. 基于元胞自动机的大气扩散模型及GIS可视化[J]. 环境工程学报, 2016, 10(5): 2527-2534. doi: 10.12030/j.cjee.201412091
引用本文: 韦宗明, 艾矫燕, 李修华, 邓超冰, 吴宗书, 蔡亚娟, 吴思知, 徐海扬. 基于元胞自动机的大气扩散模型及GIS可视化[J]. 环境工程学报, 2016, 10(5): 2527-2534. doi: 10.12030/j.cjee.201412091
shu
Wei Zongming, Ai Jiaoyan, Li Xiuhua, Deng Chaobing, Wu Zongshu, Cai Yajuan, Wu Sizhi, Xu Haiyang. Air diffusion model and GIS visualization based on cellular automata[J]. Chinese Journal of Environmental Engineering, 2016, 10(5): 2527-2534. doi: 10.12030/j.cjee.201412091
Citation: Wei Zongming, Ai Jiaoyan, Li Xiuhua, Deng Chaobing, Wu Zongshu, Cai Yajuan, Wu Sizhi, Xu Haiyang. Air diffusion model and GIS visualization based on cellular automata[J]. Chinese Journal of Environmental Engineering, 2016, 10(5): 2527-2534. doi: 10.12030/j.cjee.201412091
shu

基于元胞自动机的大气扩散模型及GIS可视化

  • 1. 广西大学电气工程学院, 南宁 530004
  • 2. 广西环境监测中心站, 南宁 530000
  • 收稿日期:  2015-09-03
基金项目:

广西科技计划自治区主席科技资金(1517-08)

广西自然科学基金重大项目(2013GXNSFEA053001)

摘要: 基于对目前常用大气扩散模型以及大气扩散特性的分析,采用通过局部转移规则实现宏观涌现的复杂系统建模工具-元胞自动机来建立时空动态的大气扩散模型。结合MATLAB的矩阵运算能力和GIS的栅格数据处理能力进行模型的实现与可视化。仿真结果表明,所建立的模型不仅能动态模拟大气污染的高斯扩散等常用扩散模式,通过合理的模型参数设定也可动态模拟非常规扩散模式,如模拟时段内风向风速发生多次变化或者模拟区域存在湍流等条件下的扩散过程,得到准确的污染物时空动态分布,可望为大气污染防治提供决策支持。

English Abstract

    全文HTML

参考文献 (25)

返回顶部

目录

/

返回文章
返回

Copyright © 2019 中国科学院生态环境研究中心