This invention discloses a method, device, and computer storage medium for predicting and actively controlling the deformation of support structures based on computational learning. It relates to the fields of
geotechnical engineering and underground structure
safety control technology. This method, based on the theory of support structure displacement calculation and combined with a theoretical calculation model, achieves accurate prediction of the horizontal displacement of the support structure, completes structural displacement calculation and dangerous area identification, and outputs deformation curves and
potential risk locations. It employs a
Bayesian optimization framework for automatic parameter optimization, initializes the prior distribution and sets the objective function, uses
Gaussian process modeling to iteratively calculate the acquisition function, and uses a
surrogate model to quickly predict performance to update the model. Finally, it outputs the optimal parameter combination to guide construction, realizing an intelligent closed-
loop design from theoretical calculation to
engineering control, and solving the problems of insufficient deformation prediction accuracy and lagging
risk control in complex strata.