首页|Investigators from University of Shanghai for Science and Technology Have Report ed New Data on Support Vector Machines (An Atpso-svm Prediction Model for Flow S tress Investigation of Lightweight Materials: a Case Study of 6181/6016h18 Alumi num ...)
Investigators from University of Shanghai for Science and Technology Have Report ed New Data on Support Vector Machines (An Atpso-svm Prediction Model for Flow S tress Investigation of Lightweight Materials: a Case Study of 6181/6016h18 Alumi num ...)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing - Support Vector Machines have been published. According to news reporting f rom Shanghai, People’s Republic of China, by NewsRx journalists, research stated , “Al-Mg-Si (6xxx series) aluminum alloys are widely employed in the automotive industry for lightweight applications, but crack formation during thermal formin g remains a common issue. To address the problem and enhance the mechanical prop erties of these materials, an in-depth study of the flow stress is crucial.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), National Natural Science Foundation of China (NSFC), Natural Science Foundation of Shanghai, Program of Foundation of Science and Technology Commission of Shanghai Municipality, Shanghai Professional Technical Service Pl atform for Intelligent Operation and Maintenance of Renewable Energy.
ShanghaiPeople’s Republic of ChinaAs iaAlloysAluminumLight MetalsMachine LearningSupport Vector MachinesU niversity of Shanghai for Science and Technology
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