Analysis of blast furnace cross thermometric based on spatial data mining

Yanchi Liu, Hongwei Guo, Xuedong Gao
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引用次数: 2

Abstract

Current clustering algorithms are limited in insufficient use of spatial information of cross thermometric temperature data. To address this problem, this paper presents a new similarity and distance measurement approach with which the spatial distance can be effectively computed. On the basis of new measurement, the clustering result of Jinan Iron and Steel 1# blast furnace cross thermometric temperature data show that the method can fully extract useful information of the temperature data and in practical applications with higher accuracy and reliability.
基于空间数据挖掘的高炉交叉测温分析
现有的聚类算法存在对交叉测温数据空间信息利用不足的问题。为了解决这一问题,本文提出了一种新的相似性和距离度量方法,可以有效地计算空间距离。在此基础上,济钢1#高炉交叉测温温度数据的聚类结果表明,该方法能充分提取温度数据的有用信息,在实际应用中具有较高的精度和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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