首页|Studies from Harbin Institute of Technology in the Area of Machine Learning Reported (Identification of the Form of Self-excited Aerodynamic Force of Bridge Deck Based On Machine Learning)
Studies from Harbin Institute of Technology in the Area of Machine Learning Reported (Identification of the Form of Self-excited Aerodynamic Force of Bridge Deck Based On Machine Learning)
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
A new study on Machine Learning is now available. According to news reporting from Harbin, People's Republic of China, by NewsRx journalists, research stated, “This paper introduces an intelligent identification method for self-excited aerodynamic equations. The method is based on advanced sparse recognition technology and equipped with a new sampling strategy designed for weak nonlinear dynamic systems with limit cycle characteristics.” Funders for this research include National Natural Science Foundation of China (NSFC), National Key Research and Development Program of China, National Natural Science Foundation of China (NSFC), Natural Science Foundation of Heilongjiang Province, Postdoctoral scientific research development fund of Heilongjiang Province, Heilongjiang Touyan Team and Fundamental Research Funds for the Central Universities. The news correspondents obtained a quote from the research from the Harbin Institute of Technology, “Considering the complexity of the experiment condition and the difficult a priori selection of hyperparameters, a method based on information criteria and ensemble learning is proposed to derive the global optimal aerodynamic self-excited model. The proposed method is first validated by simulated data obtained from some well-known equations and then applied to the identification of flutter aerodynamic equations based on wind tunnel experiments.”
HarbinPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningHarbin Institute of Technology
NETL
NSTL
