基于遗传BP神经网络的飞机驾驶舱人机功能分配方法

Abstract

飞机驾驶舱系统自动化水平提高的关键在于科学合理地进行人机功能分配。为了提高飞机驾驶舱人机功能分配的可靠性，本文通过对遗传算法和BP神经网络这两种智能算法进行分析研究，提出了基于遗传BP神经网络的飞机驾驶舱人机功能分配方法。将机组成员飞行时的生理指标HRV2和TLI2作为网络的输入变量，使用遗传算法优化BP神经网络权值和阀值，输出飞行任务自动化等级，进而得到相应的人机功能分配方案。仿真结果表明，相比于传统的BP神经网络，该方法确定的人机功能分配方案可靠性更高。 The key to improve the automation level of the aircraft cockpit system is getting on man-machine function allocation scientifically and reasonably. In order to improve the reliability of man-machine function allocation for cockpit, based on the study of genetic algorithm and BP neural network, we propose a method of using genetic BP neural network in this paper. The input variables of the network are HRV2 and TLI2 which are the physiological indexes of the crew. Geneticalgorithm was used to optimize the weights and bias of BP neural network. The output variable of the network is the levels of automation. In this way, we can get corresponding man-machine function allocation scheme. Compared with the traditional BP neural network, the simulation result shows that this method is more reliable for the man-machine function allocation.