title: Optimization of fixture layouts of glass laser optics using multiple kernel regression.
abstract: We aim to build an integrated fixturing model to describe the structural properties and thermal properties of the support frame of glass laser optics. Therefore, (a) a near global optimal set of clamps can be computed to minimize the surface shape error of the glass laser optic based on the proposed model, and (b) a desired surface shape error can be obtained by adjusting the clamping forces under various environmental temperatures based on the model. To construct the model, we develop a new multiple kernel learning method and call it multiple kernel support vector functional regression. The proposed method uses two layer regressions to group and order the data sources by the weights of the kernels and the factors of the layers. Because of that, the influences of the clamps and the temperature can be evaluated by grouping them into different layers.
authors.forename: Jianhua
authors.initials: J
authors.lastname: Su
authors.forename: Enhua
authors.initials: E
authors.lastname: Cao
authors.forename: Hong
authors.initials: H
authors.lastname: Qiao
mesh_terms: D003198:Computer Simulation; D017076:Computer-Aided Design; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005898:Glass / Q000737:chemistry*; D007834:Lasers; D007909:Lenses; D008027:Light; D015233:Models, Statistical; D012044:Regression Analysis; D012542:Scattering, Radiation; D013696:Temperature