Abstract
The research shows that projection pursuit cluster (PPC) model is able to form a suitable index for overcom-ing the difficulties in comprehensive evaluation, which can be used to analyze complex multivariate prob-lems. The PPC model is widely used in multifactor cluster and evaluation analysis, but there are a few prob-lems needed to be solved in practice, such as cutoff radius parameter calibration. In this study, a new model-projection pursuit dynamic cluster (PPDC) model-based on projection pursuit principle is developed and used in water resources carrying capacity evaluation in China for the first time. In the PPDC model, there are two improvements compared with the PPC model, 1) a new projection index is constructed based on dynamic cluster principle, which avoids the problem of parameter calibration in the PPC model success-fully; 2) the cluster results can be outputted directly according to the PPDC model, but the cluster results can be got based on the scatter points of projected characteristic values or the re-analysis for projected character-istic values in the PPC model. The results show that the PPDC model is a very effective and powerful tool in multifactor data exploratory analysis. It is a new method for water resources carrying capacity evaluation. The PPDC model and its application to water resources carrying capacity evaluation are introduced in detail in this paper.
Highlights
The difficulty frequently encountered in water resources carrying capacity evaluation is that there are so many factors and the complex interrelationship among them, which cannot be evaluated according to only one factor, all the effect factors associated with water resources carrying capacity must be thought over
In the projection pursuit dynamic cluster (PPDC) model, there are two improvements compared with the projection pursuit cluster (PPC) model, 1) a new projection index is constructed based on dynamic cluster principle, which avoids the problem of parameter calibration in the PPC model successfully; 2) the cluster results can be outputted directly according to the PPDC model, but the cluster results can be got based on the scatter points of projected characteristic values or the re-analysis for projected characteristic values in the PPC model
The PPDC model combines dynamic cluster method with projection pursuit principle, which is an effective improvement for the PPC model
Summary
The difficulty frequently encountered in water resources carrying capacity evaluation is that there are so many factors and the complex interrelationship among them, which cannot be evaluated according to only one factor, all the effect factors associated with water resources carrying capacity must be thought over. According to projection pursuit principle, many new mathematical analysis methods for high-dimensional data exploratory analysis have been developed [2,3,4,5,6,7,8], and projection pursuit cluster (PPC) model is one of them. The PPC model is an effective method for multifactor data exploratory analysis, which is widely used in multivariable prediction, cluster and evaluation [9,10,11,12,13,14,15]. In order to resolve the problem mentioned above, Wang and Ni developed a projection pursuit dynamic cluster (PPDC) model and it was used in regional partition of water resources in China [16]. The PPDC model and its application will be introduced in detail in the following
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
