The application discloses a bronchoscope supply-demand dynamic matching method based on multi-
source data fusion, comprising: collecting multi-source heterogeneous data and performing fusion
processing to obtain a device
feature matrix, a demand
feature matrix and an environment
feature vector; determining a
score calculation strategy according to a comparison result of a historical matching data accumulation amount and a preset threshold, determining a device availability
score and a demand urgency
score based on the device
feature matrix and the demand feature matrix according to the score calculation strategy; constructing a device
queue and a demand
queue, attaching an initial scene
label to each demand and performing identification, and outputting a standardized scene type; outputting an
optimal matching scheme through a
reinforcement learning intelligent agent based on the device
queue, the demand queue, the standardized scene type and the environment
feature vector; performing intelligent scheduling based on the
optimal matching scheme, updating the queue based on external real-time events, and if both queues are non-empty at the same time, obtaining a new
optimal matching scheme, otherwise, keeping a waiting state. The application can improve matching efficiency and accuracy.