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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均值算法在原生高岭土分类中的应用

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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:应用随机初始聚类中心k-Means算法分析天然高岭土的化学成分,该化学成分与天然高岭土相似,被归为一类。本文是从获得的实验结果中寻找天然高岭土的替代梯队。根据相似的高岭土相互替代的原则,本文解决了天然高岭土供应不足的问题,找到了高岭土有效利用和可持续发展的可能途径,并提出了其他陶瓷原料相互替代的思路。

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