首页|Researchers from HeNan Polytechnic University Report on Findings in Support Vect or Machines (Ensemble Learning With Support Vector Machines Algorithm for Surfac e Roughness Prediction In Longitudinal Vibratory Ultrasound-assisted Grinding)
Researchers from HeNan Polytechnic University Report on Findings in Support Vect or Machines (Ensemble Learning With Support Vector Machines Algorithm for Surfac e Roughness Prediction In Longitudinal Vibratory Ultrasound-assisted Grinding)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Current study results on Support Vector Machines have been published. According to news reporting originating from Jiaozuo, Peopl e's Republic of China, by NewsRx correspondents, research stated, "It is critica l to have an accurate prediction of surface roughness (Sa) in order to improve g rinding productivity, reduce costs, and minimize the period of time required for trials and testing. Although many prediction methods have been developed, fewer studies have been conducted on the prediction of surface roughness in longitudi nal ultrasonic vibration-assisted grinding (LUVAG)." Our news editors obtained a quote from the research from HeNan Polytechnic Unive rsity, "In this paper, a surface roughness prediction model algorithm based on e nsemble learning of support vector machines (ELSVM) is proposed that can be used for surface roughness prediction of LUVAG alumina ceramics. This paper first de tails the development of the ELSVM surface roughness prediction model, which con sists of four modules: the prepossessing module, the multi-algorithm regression module, the support vector machine algorithm (SVM) module, and the ensemble modu le. In addition, ELSVM was compared with four other machine learning methods bas ed on experimental results for surface roughness prediction modeling. The error of ELSVM model was reduced by 6.3%, 7.9%, 8.9% , and 7.5%, respectively, compared to the individual prediction mod els such as I-AISPSO, I-AIS, SPSO, and KBaNN."
JiaozuoPeople's Republic of ChinaAsi aAlgorithmsEmerging TechnologiesMachine LearningSupport Vector MachinesVector MachinesHeNan Polytechnic University
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