蚁群算法优化的神经网络技术在跑道起飞容量预测中的应用

Analysis of Airport Runway Take-Off Capacity Prediction Based on ACO Optimized BP Neural Network

为了对机场起飞容量及飞机全部出动时间进行预测,构建了基于ACO优化BP神经网络的机场跑道起飞容量预测模型。分析了机场跑道容量的含义及其影响因素,利用飞参提取软件将影响因素的具体数值进行提取;依据BP神经网络的特点将其引入到机场跑道起飞容量预测中,为了弥补BP神经网络的缺点,利用ACO对网络进行优化,最终建立了基于ACO优化BP神经网络的机场跑道起飞容量预测模型,并与标准BP神经网络的预测结果进行对比,结果表明优化后的网络各项误差都不同程度的减小40%~60%,优化后的网络提高了模型的精度。利用优化后的模型分析了飞机质量、气温、气压、风速与起飞跑道占用时间与起飞容量的关系,并对某机场保障飞机起飞容量与出动时间进行了评估,得到飞机质量、气压、纵向风速与起飞容量大致呈线性关系,气温与起飞容量大致呈非线性关系,最后得到该机场的总出动时间与起飞跑道容量,可以更准确的评估机场保障能力。

In order to predict the take-off capacity of the airport and the total departure time of the aircraft,a runway take-off capacity prediction model based on ACO optimized BP neural network was constructed.It analyzed the meaning of airport runway capacity and its influencing factors,using flight parameter extraction software to extract the specific values of influencing factors.It was introduced into the airport runway take-off capacity prediction,according to the characteristics of BP neural network.In order to make up for the shortcomings of BP neural network,it used ACO to optimize the network,and finally established an airport runway take-off capacity prediction model based on ACO optimized BP neural network,and compared with the prediction results of the standard BP neural network.The results show that the optimized network errors are of varying degree reduced by about 40%-60%,the optimized network improves the accuracy of the model.The optimized model can be used to analyze the relationship between aircraft quality,air temperature,air pressure,wind speed and take-off runway occupancy time and take-off capacity.And an airport guaranteed aircraft take-off capacity and departure time are evaluated,and the aircraft quality,air pressure,longitudinal wind speed and the take-off capacity is roughly linear,and the temperature and take-off capacity are roughly non-linear.Finally,the total departure time and take-off runway capacity of the airport can be obtained,which can assess the airport’s support capability more accurately.