Study on Classification Model of Seawater Samples with Different Pollution Sources
LIN Yan1, ZHU Er-yi1*, XU Xiao-qin1, LEE Frank S C2, WANG Xiao-ru2
1. Department of Chemistry, the Key Laboratory of Analytical Sciences of the Ministry of Education, Xiamen University, Xiamen 361005, China 2. The First Institute of Oceanography, State Oceanic Administration, Qindao 266061, China
Abstract：In the present article the principle and advantages of the method to build classification model by partial least squares are briefly introduced. The method was applied to deal with the seawater data obtained from the primary polluted sea area of Jiaozhou bay and Laizhou bay by GC-MS. The classification models have been built for seawater samples from different contaminated areas. The results indicate that PLS is very suitable for dealing with the problems with the data sets that contain many variables and few samples and have serious co-linearity. Accurate classification models can be built by use of PLS to get the classification information of pollution sources from two or many kinds of polluted seawaters data sets from GC-MS. The cross validation relativities of the model comes to over 0.91. This result is approving, which can provide a reliable foundation for distinguishing pollution sources correctly. Moreover, compared with the traditional method, the classification figures constructed by model’s ｉ in the article are more clear and intuitive, and can express the model’s discrimination effect better.
Key words：GC-MS;Partial least squares(PLS);Classification model
林燕1,朱尔一1*,徐晓琴1,LEE Frank S C2, 王小如2 . 不同污染源海水样本的分类模型研究[J]. 光谱学与光谱分析, 2007, 27(10): 2107-2110.
LIN Yan1, ZHU Er-yi1*, XU Xiao-qin1, LEE Frank S C2, WANG Xiao-ru2 . Study on Classification Model of Seawater Samples with Different Pollution Sources. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2007, 27(10): 2107-2110.
