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The parameters plays an important role to the performance of support vector regression(SVR). In order to solve the problem of the Parameter optimization for SVR, first, we transform the problem of Parameter optimization into a problem of nonlinear system state estimation, then, we propose a novel algorithm based on Dual Recursive Variational Bayesian Adaptive Square-Cubature Kalman Filter (DRVB-ASCKF),...
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