Multi-Response Weighted Adaptive Sampling Approach Based on Hybrid Surrogate Model

In order to improve the fitting accuracy and optimization efficiency of surrogate model, a multi-response weighted adaptive sampling (MWAS) approach based on hybrid model was proposed implemented multi-objective lightweight design car seats. this approach, sample discreteness index in input space calculated by maximum minimum distance (MDA), uncertainty output response strategy prediction variance (WPV), two indices are combined weight coefficients. iterative process, coefficients were determined according model. The balance global local realized considering dispersion comprehensively. Numerical examples single-response systems showed that has excellent robustness. Moreover, results actual engineering application constructed through MWAS could significantly optimization. Hence, high-precision solution passenger rear seat obtained.