Application of Random Initial Cluster Center K-Means Algorithm to Native Kaolin Classification

Random initial cluster center k-Means algorithm is applied to analyze the chemical composition of the native Kaolin, which is similar to the native kaolin and is classified into one class. This paper is to find the alternative echelon of native Kaolin from the obtained experimental results. According to the principle of similar Kaolin replacing each other, the paper solves the problem of insufficient supply of native Kaolin, finds possible ways to Kaolin´s efficient use and sustainable development, and suggests ideas for other porcelain raw materials´ replacing each other.