The invention discloses a self-adaptive
shunting decision method based on a
control theory and data driving, and the method comprises the steps: defining a proper network environment as the state input of an
intelligent agent module, and enabling an
intelligent agent to make an action decision in a self-adaptive manner through the training and testing process of a
machine learning model; distributing a corresponding number of video data to the transmission terminal after the optimal distribution ratio of the multiple paths is decided; meanwhile, calculating the
code rate control range based on a dynamic
change model of the buffer area, adjusting the video
code rate to adapt to the change of occupation of the buffer area, and therefore, the video playing fluency is guaranteed; through the
control system, further optimizing the application accuracy of the
machine learning
algorithm decision model in an actual
system; and in a
system test stage, transmitting corresponding video data by using an optimal split ratio, calculating a video
code rate range, and selecting a proper value by a
control system to be matched with the dynamically changing buffer area occupation length.