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During the combustion process of hot blast stove, controlling the steady rise of vault temperature and flue gas temperature is an important link. A large amount of data is preprocessed in the field, and the kernel-based clustering algorithm is used to optimize the combustion control process of hot blast stove. The experimental results show that the algorithm has high accuracy and fast convergence. Compared with the traditional combustion control method, the improved method has better optimization effect and better stability.