... in future iterations. We show that query type 1 can be considered as an active learning problem, while type 2 as a “black-box” optimization problem. This paper concentrates on query type 2. Two algorithms based on support vector machine and efficient global optimization search are presented and discussed...

... design optimization. 02 02 2011 24 08 2011 28 10 2011 28 10 2011 electric vehicles mechanical engineering computing power transmission (mechanical) product design support vector machines decomposition-based design optimization reduced representation constraint...

... description is complicated by the characteristics of observational data sets, which can contain small numbers of samples, can have nonlinear associations among the variables, can be nonconvex, and can occur in disjoint clusters. Support vector machine (SVM) techniques, developed originally in the machine...

... optimization (RDBO) problem under the assumption of truncated normal distributions of the geometric properties. The solution is obtained by first constructing the explicit boundaries of the failure regions (limit state function) using a support vector machine, combined with adaptive sampling and uniform design...

... , Prentice Hall , Upper Saddle River, NJ. Cristianni , N. , and Shawe-Taylor , J. , 2000 , An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods , Cambridge University Press , Cambridge, UK. Hearst , M. A. , 1998 , “ Trends Controversies: Support Vector...