  Try to generate new bridge types using generative artificial intelligence
technology. The grayscale images of the bridge facade with the change of
component width was rendered by 3dsMax animation software, and then the OpenCV
module performed an appropriate amount of geometric transformation (rotation,
horizontal scale, vertical scale) to obtain the image dataset of three-span
beam bridge, arch bridge, cable-stayed bridge and suspension bridge. Based on
Python programming language, TensorFlow and Keras deep learning platform
framework, variational autoencoder was constructed and trained, and
low-dimensional bridge-type latent space that is convenient for vector
operations was obtained. Variational autoencoder can combine two bridge types
on the basis of the original of human into one that is a new bridge type.
Generative artificial intelligence technology can assist bridge designers in
bridge-type innovation, and can be used as copilot.
