基于熵权-FCM的区域管制席亚健康状态划分方法

对区域管制席亚健康状态进行合理划分是管制运行系统采取有效管控措施的基础,对衡量管制员绩效和评估空域运行状态具有重要的意义。基于管制员工作负荷选取5项评价指标,针对各评价指标对区域管制席亚健康状态的影响程度不同,提出一种基于熵权-FCM的区域管制席亚健康状态划分方法。该方法利用信息熵对区域管制席亚健康状态评价指标赋权,以加权欧氏距离改进FCM目标函数,从而提高了模糊划分的清晰程度和聚类算法的收敛性,并利用划分系数、划分熵系数、改进的划分系数、目标函数和迭代次数评估了改进前后FCM算法的有效性,将区域管制席亚健康状态划分为健康、通话亚健康、设备操作亚健康。实例仿真结果表明:基于熵权-FCM的区域管制席亚健康状态划分方法能对区域管制席亚健康状态进行合理划分,且收敛性能较好。

Sub-health State Classification Method of Area Control Position Based on Entropy-FCM Algorithm

The proper classification of the area control position sub-health state is the basis for the control operate system to take effective management and control measures,which is of great significance for measuring controller performance and evaluating airspace operational status.Based on the controller’s workload,this paper selects five evaluation indictors,and proposes FCM algorithm with entropy weighting to divide sub-health state of area control position.The entropy weight method is used to characterize the difference of importance between the evaluation indictors.The FCM objective function is improved by weighted Euclidean distance,which improves the clarity of fuzzy division and the convergence of the clustering algorithm.The paper also evaluates the effectiveness of the FCM algorithm before and after improvement by the partition coefficient,the partition entropy coefficient,the improved partition coefficient,the objective function and the number of iterations.The area control sub-health state is divided into health,call sub-health,and equipment operation sub-health.Example simulation results show that the proposed method can effectively divide the area control sub-health state and has better convergence performance.