基于自动机器学习的航天测控网频谱分配方法

his paper proposes a spectrum allocation method based on automatic machine learning algorithms. The automatic machine learning algorithm based on Bayesian optimization search strategy has shown good performance in spectrum recognition. Based on its characteristics, this paper applies it to predict network traffic and thus completes the task of spectrum allocation for the communication model of the aerospace TT&C network. The experimental results show that applying automatic machine learning algorithms to spectrum allocation, although the main indicators such as network resource utilization rate and network bandwidth blocking rate are slightly inferior to the adaptive path idle degree algorithm with good recognition performance and manual parameter tuning, it still has strong practicality given that it can avoid the tedious and trivial manual parameter tuning work.