The application discloses a
laser microwave hybrid communication adaptive modulation method based on
machine learning, comprising: acquiring a
weather data set, and establishing a channel state set according to
weather data in the
weather data set; training a
random forest model RFM by using the weather
data set and the channel state set, and obtaining the trained
random forest model RFM; acquiring real-time weather data, inputting the weather data into the trained
random forest model RFM, and obtaining a current optimal channel state D i ; judging whether an average error rate P i under the
current channel state D e is less than a target error rate P e,obj , if not, adjusting the random forest model RFM until the current average error rate P e is less than the target error rate P e,obj , and simultaneously judging whether the currently executed channel state is consistent with the optimal channel state, if not, executing channel
state switching, and completing switching of the
laser microwave hybrid link. The influence of
bad weather on the channel is reduced, and the communication efficiency is improved.