摘要
根据空中交通管制员工作的特点,以时间为度量量化了管制员工作负荷,并分析了进离场飞行架次对于管制员工作负荷的影响。以进离场飞行架次为自变量,管制员工作时间为因变量,首次采用神经网络建立管制员工作负荷非线性回归模型;针对BP算法的缺点,提出了改进的BP算法;最后应用回归模型,结合DORATASK方法实现了对昆明终端区空域的容量评估。
According to the features of air traffic controllers＇ work,this paper quantifies the workload in time dimension,and analyzes the impact of the approach and departure flight numbers on controllers＇ workload.An air traffic controller non-linear regression model is established for first time based on the neural network,with the approach and departure flight movements as the independent variables and the controllers＇ working hours as the dependent variables.Aiming at the disadvantages of BP algorithm,this paper presents an improved BP algorithm.Applying the regression model and the DORATASK method,this paper evaluates the airspace capacity of the terminal area of Kunming.
出处
《交通信息与安全》
2012年第1期144-147,共4页
Journal of Transport Information and Safety
