A Dual Iterative Clustering Based Fuzzy Projection Pursuit Clustering Algorithm

This paper presents a new fuzzy projection pursuit clustering (FPPC) algorithm. FPPC is a combination of the fuzzy clustering iteration (FCI) algorithm and the projection pursuit clustering algorithm. In this paper, we adopted a new projection index function formed by the standard deviation of projection values and the quadratic sum of Euclidean distance between projection values. The new projection index function can avoid the qualitative selection of the Density Window Width, which is generally determined by experience. After lowering the dimension of sample data using projection technology, the FPPC algorithm takes a dual iterative clustering approach with FCI and PPC. In the FPPC solution process, the chaotic culture differential evolution (CCDE) algorithm formed by the chaos theory, cultural algorithm and differential evolution algorithm is adopted. Experimental simulations show that FPPC algorithm has higher clustering precision and effectiveness.