A hybrid semi-supervised regression based machine learning method for predicting peak wind loads on a group of buildings

•Proposes hybrid machine learning method SEC to assess peak wind loads on buildings.•The SEC method integrates the SSR, ELM, and CFD methods.•SEC uses SSR to expand limited wind tunnel samples to improve prediction precision.•SEC has better prediction precision than ELM trained based on limited existing samples.