首页|Findings on Support Vector Machines Detailed by Investigators at University of Electronic Science and Technology of China (A Novel Hybrid Adaptive Framework for Support Vector Machine-based Reliability Analysis: a Comparative Study)
Findings on Support Vector Machines Detailed by Investigators at University of Electronic Science and Technology of China (A Novel Hybrid Adaptive Framework for Support Vector Machine-based Reliability Analysis: a Comparative Study)
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NETL
NSTL
Elsevier
Current study results on Support Vector Machines have been published. According to news reporting originating in Chengdu, People’s Republic of China, by NewsRx journalists, research stated, “This study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVMMCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming.” Funders for this research include National Natural Science Foundation of China (NSFC), Sichuan Science and Technol-ogy Program, China Postdoctoral Science Foundation, Guangdong Basic and Applied Basic Research Foundation, Students Go Abroad for Scientific Research and Internship Funding Program of University of Electronic Science and Technology of China.
ChengduPeople’s Republic of ChinaAsiaEmerging TechnologiesEngineeringMachine LearningSupport Vector MachinesVector MachinesUniversity of Electronic Science and Technology of China
NETL
NSTL
Elsevier
