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https://www.researchgate.net/publication/227092398_Design_optimization_using_support_vector_regression
Polynomial regression (PR) and kriging are standard meta-model techniques used for approximate optimization (AO). Support vector regression (SVR) is a new meta-model technique with higher accuracy ...
https://link.springer.com/article/10.1007/s12206-007-1027-4
Polynomial regression (PR) and kriging are standard meta-model techniques used for approximate optimization (AO). Support vector regression (SVR) is a new meta-model technique with higher accuracy and a lower standard deviation than existing techniques. In this paper, we propose a sequential approximate optimization (SAO) method using SVR.Cited by: 14
https://www.sciencedirect.com/science/article/pii/S0263876212002468
The optimization method using support vector regression (SVR) models and information analysis for design of experiment (SIDOE) in Section 5 has been used in two cases to optimize the operational conditions of the simulated atmospheric distillation column (ADC) in Section 2.Cited by: 13
https://www.sciencedirect.com/science/article/pii/S1270963819303621
This paper investigates a structural optimization for the non-circular vent hole on an aero-engine turbine disk. A novel optimization approach, namely SO-ISVR (the surrogate-based optimization using an improved support vector regression), for the vent hole design is developed.Author: Cheng Yan, Zeyong Yin, Zeyong Yin, Xiuli Shen, Dong Mi, Fushui Guo, Dan Long
https://asmedigitalcollection.asme.org/mechanicaldesign/article/127/6/1077/478236/Analysis-of-Support-Vector-Regression-for
Aug 13, 2004 · In this paper, we investigate support vector regression (SVR) as an alternative technique for approximating complex engineering analyses. The computationally efficient theory behind SVR is reviewed, and SVR approximations are compared against the aforementioned four metamodeling techniques using a test bed of 26 engineering analysis functions.Cited by: 473
https://www.scholars.northwestern.edu/en/publications/use-of-support-vector-regression-in-structural-optimization-appli
This paper presents two industrial cases using support vector regression (SVR) for vehicle crashworthiness design. ... Zhang, Siliang. / Use of support vector regression in structural optimization : Application to vehicle crashworthiness design. In: Mathematics and ... Use of support vector regression in structural optimization. T2 ...Cited by: 20
https://link.springer.com/article/10.1007%2Fs00158-017-1658-8
Jan 31, 2017 · Variable stiffness composite material design by using support vector regression assisted efficient global optimization method. Authors; Authors and affiliations ... Design optimization using support vector regression. J Mech Sci Technol 22(2 ... (2006) Robust classification and regression using support vector machines. Eur J Oper Res 173(3):893 ...Cited by: 10
https://www.mathworks.com/help/stats/understanding-support-vector-machine-regression.html
Understanding Support Vector Machine Regression Mathematical Formulation of SVM Regression Overview. Support vector machine (SVM) analysis is a popular machine learning tool for classification and regression, first identified by Vladimir Vapnik and his colleagues in 1992.SVM regression is considered a nonparametric technique because it relies on kernel functions.
https://asmedigitalcollection.asme.org/mechanicaldesign/article/133/4/041002/431976/Integrating-Least-Square-Support-Vector-Regression
Therefore, in this work, we integrate the least support vector regression (LSSVR) with the mode pursuing sampling (MPS) optimization method and applied the integrated approach for crashworthiness design.Cited by: 14
http://connection.ebscohost.com/c/articles/96032140/data-driven-modeling-optimization-cavity-filters-using-linear-programming-support-vector-regression
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