Projection pursuit cluster model and its application in water quality assessment.
One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must be used. In order to overcome this issues the projection pursuit principle is introduced into water quality assessment, and projection pursuit cluster (PPC) model is developed in this study. The PPC model makes the transition from high dimension to one-dimension. In other words, based on the PPC model, multifactor problem can be converted to one factor problem. The application of PPC model can be divided into four parts: (1) to estimate projection index function Q(a -->); (2) to find the right projection direction a -->; (3) to calculate projection characteristic value of the i th sample z(i), and (4) to draw comprehensive analysis on the basis of z(i). On the other hand, the empirical formula of cutoff radius R is developed, which is benefit for the model to be used in practice. Finally, a case study of water quality assessment is proposed in this paper. The results showed that the PPC model is reasonable, and it is more objective and less subjective in water quality assessment. It is a new method for multivariate problem comprehensive analysis.
Wang
Shun-Jiu
SJ
School of Environment, Beijing Normal University, Beijing 100875, China. wsjbnu@163.com.cn
Yang
Zhi-Feng
ZF
Ding
Jing
J
D004784:Environmental Monitoring / Q000379:methods*; D008962:Models, Theoretical; D015999:Multivariate Analysis; D011786:Quality Control; D014873:Water Pollutants / Q000032:analysis*
D014873:Water Pollutants