基于量子门线路神经网络的射击试验安全风险评估

为提高射击试验安全,在分析现有安全管理机制基础之上,结合射击试验安全管理实践经验,采用量子旋转门控制量子位的翻转与相位的偏转,建立风险评估指标模型,通过仿真实验来验证文章所采取研究方法的有效性,并与传统BP神经网络性能进行风险评估精度的比较;通过分析及比较,文章构建的量子门线路模型降低了安全试验相关数据处理的复杂度,对射击试验安全风险评估的收敛速度更高,提高了对射击试验过程中安全风险的预测精度,为射击试验相关管理人员评估试验危险及制定措施提供了理论依据.

Safety risk assessment of shooting test based on quantum gate circuit neural network

In order to improve the safety of shooting tests, combined with the practical experience of safety management, a quantum revolving gate is used to control the deviation of the rotation of the qubits from the phase to calculate the comprehensive risk value for transforming the safety of shooting tests. The effectiveness of the proposed method is verified through simulation experiments. The integrated quantum gate circuit model here has a higher convergence speed for the safety risk assessment of the shooting test, and reduces the complexity of data processing and improves the accuracy of the risk assessment. The relevant management personnel provided a theoretical basis for evaluating the test risks and formulating measures.