With the development of automation and informatization in the steelmaking industry, the
human brain gradually fails to cope with an increasing amount of data generated during the …

Basic oxygen furnace (BOF) steelmaking is the most widely used process in global steel
production today, accounting for around 70% of the industry's output. Due to the physical …

The machine learning models of multiple linear regression (MLR), support vector regression
(SVR), and extreme learning machine (ELM) and the proposed ELM models of online …

Defect engineering of semiconductor photocatalysts is critical in reducing the reaction
barriers. The generation of surface oxygen vacancies allows substantial tuning of the …

Precise control of the end-point phosphorus and sulfur content in converter steelmaking is
critical to ensuring steel quality. An end-point prediction model based on LWOA-TSVR is …

In this article, main process data, notably time–series data such as lance position patterns,
are analyzed during converter steelmaking, and methodologies in data processing and …

In this study, we investigate the burning behavior of titanium during the electroslag remelting
(ESR) process and its impact on the titanium content at the endpoint using machine …

The basic oxygen furnace (BOF) steelmaking processes with complex multiphase reactions
can be modeled by data-driven technique, but it is particularly difficult to predict the end …

Mathematical (data-driven) models based on state-of-the-art (SOTA) machine learning and
deep learning models and data collected from 12,786 heats were established to predict the …

This study developed a Bayesian optimisation-enhanced fully connected neural network
(BO-EFCNN) model with an early stopping mechanism to predict the end-point carbon …