论文信息 - Application of the Fuzzy C-Means Clustering Algorithm for the Burden Distribution Matrix of Blast Furnace

Application of the Fuzzy C-Means Clustering Algorithm for the Burden Distribution Matrix of Blast Furnace

Burden distribution matrix is the key to guarantee the long-term stable production of the blast furnace. The optimization of the burden distribution matrix aims to form a reasonable burden surface. It can help to achieve the goal of smooth, high-quality and low-consumption blast furnace production. This paper uses the blast furnace condition parameter to measure the burden distribution matrix. And these data is characterized by panel data in statistics. The fuzzy c-means algorithm is used to cluster. Finally, evaluation indicators are using to analyze the clustering effect. It has important reference value for the blast furnace actual production.

Yixin Yin | Sen Zhang | Xiaoli Su | Yuanzhe Hui

[1] Qiang Li,et al. A hybrid classical-quantum clustering algorithm based on quantum walks , 2011, Quantum Inf. Process..

[2] Augusto Y. Hermosilla,et al. Clustering Panel Data via perturbed Adaptive Simulated Annealing and Genetic Algorithms , 2002, Adv. Complex Syst..

[3] Li Bang-yi,et al. The Discussion on the Clustering Way Based on the Multi-dimensional Panel Data and Empirical Analysis , 2009 .

[4] J. C. Dunn,et al. A Fuzzy Relative of the ISODATA Process and Its Use in Detecting Compact Well-Separated Clusters , 1973 .

[5] Du-Ming Tsai,et al. Fuzzy C-means based clustering for linearly and nonlinearly separable data , 2011, Pattern Recognit..

[6] Richard J. Hathaway,et al. Density-Weighted Fuzzy c-Means Clustering , 2009, IEEE Transactions on Fuzzy Systems.

[7] Miguel A. Juárez,et al. Model-Based Clustering of Non-Gaussian Panel Data Based on Skew-t Distributions , 2010 .

[8] Jian Huang,et al. Identification of the Optimal Control Center for Blast Furnace Thermal State Based on the Fuzzy C-means Clustering , 2011 .