A projection pursuit dynamic cluster (PPDC) model is proposed, which combines projection pursuit principle with dynamic cluster rule. Firstly, multifactor cluster problem is converted into single-factor cluster problem according to linear projection technique. Secondly, a new projection index based on dynamic cluster rule is constructed in the PPDC model, which would finish the sample clustering based on the projected characteristic value. In comparison with the existing projection pursuit cluster (PPC) model, we construct a new projection index based on dynamic cluster method in the PPDC model, which successfully avoids the problem of parameter calibration in the PPC model and makes the cluster results more objective. On the other hand, the cluster results can be outputted directly according to the PPDC model, but in the PPC model the cluster results can be got using other method to re-analyze projected characteristic values. A case study of groundwater classification is given at last, and the results show that the PPDC model is reasonable and easy to operate in practice. The PPDC model is a new method for multifactor cluster analysis and has a bright future in cluster analysis field.
