Research on AOD furnace end-point temperature prediction based on sparrow search algorithm optimization ELM

Lei Yang; Lin Chai; Huikang Liu; Zhen Yi

doi:10.1117/12.2667481

28 March 2023 Research on AOD furnace end-point temperature prediction based on sparrow search algorithm optimization ELM

Lei Yang, Lin Chai, Huikang Liu, Zhen Yi

Author Affiliations +

Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 125661D (2023) https://doi.org/10.1117/12.2667481
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China

Abstract

In order to make the endpoint temperature prediction hit rate and velocity meet the requirements, in this paper, the Extreme Learning Machine (ELM) is used to build a model which predicts the endpoint temperature of the AOD refining furnace, and the model is trained with the real production data to search the nonlinear variation law between the input quantity and the endpoint temperature. The Sparrow Search Algorithm (SSA) is used to adjust the parameters of model to improve the hit rate of ELM. By comparing with other prediction models, found that the model is better than the pre-optimized temperature model in prediction hit rate and better than Support Vector Regression (SVR) in prediction velocity, which is more suitable for guiding actual production.

Citation Download Citation

Lei Yang, Lin Chai, Huikang Liu, and Zhen Yi "Research on AOD furnace end-point temperature prediction based on sparrow search algorithm optimization ELM", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 125661D (28 March 2023); https://doi.org/10.1117/12.2667481

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