基于贝叶斯网络的组网参数自动规划方法

Automatic Planning of Networking Parameters Based on Bayesian Network

针对战场机动通信网络快速规划需求,提出了一种基于贝叶斯网络的组网参数自动规划方法。通过对传统二进制粒子群优化算法在粒子群初始化和算法搜索空间等方面进行改进,实现了组网参数贝叶斯网络结构的快速学习,利用贝叶斯网络实现组网参数的自动规划,以超短波电台网络为仿真模型,对算法进行了仿真验证。结果表明,该算法在超短波组网参数规划中具有较高的准确率,能够满足战场机动通信网络快速规划需求。

Aiming at the rapid planning requirements of manoeuvring communication network in the battlefield,the automatic planning method of networking parameters based on Bayesian network is proposed.Firstly,the traditional binary particle swarm optimization algorithm is improved in particle swarm initialization and algorithm search space,in order to realize the rapid Bayesian network learning of networking parameters.Secondly,the automatic planning of networking parameters is realized based on Bayesian network.Finally,the simulation verification of the algorithm is done by using the ultra-short wave radio network as a simulation model.The results show that the algorithm is of great accuracy in ultra-short wave networking parameters planning and meets the needs of rapid planning of manoeuvring communication network in the battlefield.