This invention aims to provide a method for optimizing a precision air supply system based on deep learning, so as to solve the problems existing in the prior art. The invention provides a method for optimizing a precision air supply system based on deep learning. It trains a prediction model based on environmental parameters.
The prediction model is used to acquire and predict the operation information of a GIS cabinet, and generate an index detection result.
The index detection result is used to perform optimal control on the precision air supply system. The invention can provide optimal solutions based on real-time feedback from temperature and humidity sensing probes, and realize accurate control of the air supply system.
METHOD FOR OPTIMIZING PRECISION AIR SUPPLY SYSTEM BASED ON DEEP LEARNING
