首页|Researchers from Xi’an Technological University Report Details of New Studies and Findings in the Area of Support Vector Machines (Fault Diagnosis of High-speed Rolling Bearing In the Whole Life Cycle Based On Improved Grey Wolf Optimizer-least ...)
Researchers from Xi’an Technological University Report Details of New Studies and Findings in the Area of Support Vector Machines (Fault Diagnosis of High-speed Rolling Bearing In the Whole Life Cycle Based On Improved Grey Wolf Optimizer-least ...)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Elsevier
A new study on Support Vector Machines is now available. According to news originating from Xi’an, People’s Republic of China, by NewsRx correspondents, research stated, “Under the high-speed condition, the fault diagnosis of rolling bearing is difficult due to parameter limitation and local optimization. To solve these problems, a fault diagnosis method of the whole life cycle based on wavelet thresholding denoising, genetic algorithm-variational mode decomposition (GA-VMD) and improved grey wolf optimizer-least squares support vector machines (IGWO-LSSVM) is proposed.”
Xi’anPeople’s Republic of ChinaAsiaEmerging TechnologiesMachine LearningSupport Vector MachinesVector MachinesXi’an Technological University
NETL
NSTL
Elsevier
