RSAL-iMFS: A framework of randomized stacking with active learning for incremental multi-fidelity surrogate modeling

Zongqi Liu, Xueguan Song, Chao Zhang, Yunsheng Ma, Dacheng Tao

Abstract: Highlights•A QBC-based active learning method is used to select informative HF samples.•Random projections capture the characteristics of LF samples from different views.•The trained MFS model is incrementally updated by only using new HF samples.