Abstract
New research on Artificial Intelligence is the subject of a report. According to news reporting out of Beijing, People's Republic of China, by NewsRx editors, research stated, “The mechanical properties serve as crucial quality indicators for cold-rolled strips. For a long time, the mechanical properties mechanism and data-driven models can't comprehensively consider sufficient factors to achieve high-accuracy prediction due to the 'data-isolated island' between production lines.” Our news journalists obtained a quote from the research from the University of Science and Technology Beijing, “In this research, we introduce a multi-process collaborative platform based on the industrial internet system. This platform is designed to enable real-time collection of diverse and heterogeneous data from both upstream and downstream processes of cold rolling. On this basis, a novel mechanical properties interval prediction model is proposed using the sparrow search algorithm to optimize fast learning network under the LUBE framework. We trained the model by using a dataset collected from a large steel plant. Based on the rolling theory and Pearson correlation coefficient, 25 features are selected as the inputs of the prediction model.”
NETL
NSTL