The invention relates to the technical field of optical line terminal configuration, in particular to a method and
system for automatically configuring optical line terminals of different manufacturers based on
artificial intelligence. The method comprises the steps of collecting multi-source heterogeneous data to
train a
deep learning model, constructing a Transform or RNN-based architecture of a TensorFlow framework, performing
cross validation and
model compression, then performing optimization through a TensorRT
inference engine, developing an intelligent configuration application
system, deploying the intelligent configuration application
system to a control host, and providing
algorithm support for automatic configuration. By constructing an automatic
configuration system based on
artificial intelligence, the problems of heterogeneous compatibility and intelligent configuration of OLT equipment of multiple manufacturers are systematically solved. In a
configuration optimization link, a virtual
simulation environment is constructed based on a real
network topology, a configuration effect is evaluated through multi-dimensional indexes such as
throughput and time
delay, potential conflicts are detected in combination with an AI
algorithm, an optimization scheme is generated, and the configuration error rate of manual operation is reduced.