  This paper presents a novel deep learning model based on the transformer
architecture to predict the load-deformation behavior of large bored piles in
Bangkok subsoil. The model encodes the soil profile and pile features as
tokenization input, and generates the load-deformation curve as output. The
model also incorporates the previous sequential data of load-deformation curve
into the decoder to improve the prediction accuracy. The model also
incorporates the previous sequential data of load-deformation curve into the
decoder. The model shows a satisfactory accuracy and generalization ability for
the load-deformation curve prediction, with a mean absolute error of 5.72% for
the test data. The model could also be used for parametric analysis and design
optimization of piles under different soil and pile conditions, pile cross
section, pile length and type of pile.
