基于空间数据挖掘的高炉交叉测温分析

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

摘要

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。
Analysis of blast furnace cross thermometric based on spatial data mining
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.
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