首页|New Machine Learning Findings from Federal University Rio Grande do Sul Outlined (Machine Learning Applied To Predict the Flow Curve of Steel Alloys)
New Machine Learning Findings from Federal University Rio Grande do Sul Outlined (Machine Learning Applied To Predict the Flow Curve of Steel Alloys)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news reporting from Porto Alegre, Brazil, by NewsRx jour nalists, research stated, “This study aims to employ machine learning, specifica lly artificial neural networks (ANNs), to predict the flow curve of hot-deformed steel alloys. The method involved creating a dense ANN with two hidden layers, trained with data from 70 steel classes, including information on chemical compo sition, temperature, and strain rate.” Funders for this research include Conselho Nacional de Desenvolvimento Cientific o e Tecnologico (CNPQ), Coordenacao de Aperfeicoamento de Pessoal de Nivel Super ior (CAPES). The news correspondents obtained a quote from the research from Federal Universi ty Rio Grande do Sul, “The results indicate robustness and good generalization c apability, with a mean absolute error of 11.4 MPa and a mean squared error of 10 .3 MPa. The model demonstrates an R2 value of 0.98, highlighting its effectivene ss in explaining variability in the data.”
Porto AlegreBrazilSouth AmericaAll oysCyborgsEmerging TechnologiesMachine LearningFederal University Rio Gr ande do Sul
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