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A Novel Analysis of Furnace Condition Based on Biclustering

机译:基于双簇分析的炉况分析

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In the blast furnace iron-making, furnace condition is directly related to the production efficiency and blast furnace life. Currently, the analysis of furnace condition is mainly based on the artificial experience. Further progress does not exist in the analysis of furnace condition due to the difficulty of the mechanism modeling. In this paper, the biclustering algorithm is applied to the analysis of furnace condition, which is more suitable for the analysis of high dimensional data and has the ability to deal with large-scale data. First, the rank Order-Preserving Submatrix (r-OPSM) algorithm based on hierarchical search is proposed, which improves the robustness of OPSM algorithm to noise and is used for correlation analysis among multiple blast furnace conditions. On this basis, the novel concept of intermediate furnace condition is pointed out, which lays a theoretical foundation for further analysis of the state of the furnace.
机译:在高炉炼铁中,炉况直接关系到生产效率和高炉寿命。目前,炉况的分析主要基于人工经验。由于机理建模的困难,在炉况分析中没有进一步的进展。本文将二类聚类算法应用于炉况分析,该算法更适合于高维数据的分析,并且具有处理大规模数据的能力。首先,提出了一种基于分层搜索的秩序保留子矩阵(r-OPSM)算法,提高了OPSM算法对噪声的鲁棒性,并用于多种高炉条件之间的相关性分析。在此基础上,指出了中间炉状态的新概念,为进一步分析炉的状态奠定了理论基础。

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