基于模糊聚类的PM_(2.5)拟合组分选择模型的研究  

The fitting component selection model of PM_(2.5) based on fuzzy clustering

作　　者：徐恒鹏 李岳[1,2] 史国良[3] 王玮[1,2] 轩淑艳 

机构地区：[1]南开大学计算机与控制工程学院,天津300071 [2]南开大学软件学院,天津300071 [3]南开大学环境科学与工程学院国家环境保护城市空气颗粒物污染防治重点实验室,天津300071 [4]河北省唐山市玉田县环境保护局,河北唐山064199

出　　处：《中国环境科学》2016年第1期12-17,共6页China Environmental Science

摘　　要：提出了一种新的PM2.5源成分谱拟合组分选择模型,在充分考虑拟合过程的物理意义的基础上,采用聚类正确率作为组分选择的依据.实验验证,该模型能够准确获取较好的拟合主组分,相比与经验选或者手动盲选所得拟合结果,我们提出的模型将成功拟合（误差范围在0~0.05之间）的比例由40%提升到83%.In current research, there is a lack of uniform standards for components selection in PM2.5 source profile apportionment. Researchers tend to choose the component manually and empirically, leading to a subsequent poor fitting result, or even failures. Concerning on this problem, this paper has proposed an innovative component selection model of PM2.5 source profiles apportionment. On the basis of the physical representative of each component, the proposed model calculates the accuracy of fuzzy clustering as the standard score for selection. The experiments prove that our model outperforms the traditional empirical models. The successful rate for fitting, measured by the fitting errors in 0 to 0.05, grows to 83% by implementing our model, in contrast to rate of 40% from the traditional selection model.

关 键 词：PM2.5源成分谱 组分选择 CMB受体模型 源解析 模糊聚类 

分 类 号：X513[环境科学与工程—环境工程]