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

机译:随机初始聚类中心K-MEAR算法在原生Kaolin分类中的应用

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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.
机译:随机初始簇中心K-Means算法应用于分析天然高岭土的化学成分,其类似于天然高岭土,分为一类。本文是从获得的实验结果中找到天然高岭土的替代梯队。根据类似Kaolin互相取代的原则,本文解决了天然高岭土供应不足的问题,为高岭土的有效使用和可持续发展提供了可能的方法,并为其他瓷原料互相更换的思想。

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