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In order to improve the heating quality of steel and reduce the energy consumption, a method is proposed to optimize the furnace operating parameters based on historical heating data. Taking reducing the section temperature difference and fuel consumption as the goal, this method optimizes the furnace pressure, furnace temperature and other operating parameters. Based on this method, an operating parameter optimization recommender system is constructed, which can analyze and present the recommendation results interactively and dynamically according to processing rules and evaluation weights. After the system is deployed in the heating furnace of a steel mill, the historical data are used for analysis and verification, and the performance requirements of reducing section temperature difference and fuel consumption are met.