| ID | 原文 | 译文 |
| 11694 | 引入基于质心距离和重复感知率的虚拟力改进模型,综合考虑虚拟向心力和切向力对感知角度调整的影响,建立微观虚拟力与转动角度的关系模型。 | Based on centroid distance and repeated awareness rate was improved virtual force model, considering the virtual centripetal force and tangential force influence on cognitive Angle adjustment, to establish the micro virtual force and rotation Angle relation model. |
| 11695 | 并根据网络整体覆盖率增长率对节点调整幅度进行宏观控制,合理调整节点感知方向。 | And according to the network overall coverage rate of node macro control and adjustment, reasonably adjust the nodes sense of direction. |
| 11696 | 在此基础上,根据节点重复感知率和能量因素建立学习自动机与环境信息的交互机制,学习最优的冗余节点休眠调度策略。 | On this basis, according to node repeated awareness rate and energy factors to establish learning automata and interaction mechanism of environmental information, study the optimal redundant nodes sleep scheduling strategy. |
| 11697 | 仿真实验结果表明,该算法能够显著增强网络覆盖,并有效地控制网络覆盖冗余。 | The simulation results show that the proposed algorithm can significantly enhance the network coverage, and effectively control network coverage redundancy. |
| 11698 | 针对传统超视距空战威胁评估不能根据各类威胁因素的变化动态调整其对应权值的问题,引入前向反馈(back propagation,BP)神经网络。 | In view of the traditional beyond visual range air combat threat assessment based on the dynamic changes of various types of threats to the problem of the corresponding weights of the introduction of the forward feedback back propagation of BP neural network. |
| 11699 | 采用综合考虑主客观因素的结构熵权法确定各威胁指数权值并作为神经网络训练参数进行训练,提出了改进萤火虫算法(improved glowworm swarm optimization,IGSO)和BP神经网络相结合的空战动态权值计算方法。 | Considering the structure of the subjective and objective factors of entropy method is used to determine the threat index weights for neural network training and parameters to train, proposed to improve the firefly algorithm (improved glowworm swarm optimization, IGSO) and BP neural network combining the dynamic weight calculation method of air combat. |
| 11700 | 该算法采用改进萤火虫算法优化BP网络的权值和阈值,优化后的BP网络能更好地计算不同态势下的威胁指数权值,从而根据威胁估计模型进行威胁评估。 | The algorithm with the improved firefly algorithm to optimize BP network weights and threshold, the optimized BP network can better calculation under different situation, the threat of index weight, and according to the threat estimation model for threat assessment. |
| 11701 | 以某一时刻预测多无人机空中对抗时的威胁度为想定,分别采用结构熵权法和IGSO-BP进行仿真计算。 | Predict more drones at a certain moment in air combat threat degree to want to decide, respectively, the entropy weight method is adopted and IGSO - BP simulation calculation. |
| 11702 | 结果表明:结构熵权法能够科学合理地计算各威胁指数权值,IGSO-BP算法可有效解决空战目标威胁评估问题。 | The results show that the calculated structure entropy weight method can scientifically threat index weights, IGSO - BP algorithm can effectively solve the problem of air targets threat evaluation. |
| 11703 | 且所提算法与现有几种算法相比在可靠性和准确性上都有明显提高。 | And the proposed algorithm is compared with several existing algorithms on the reliability and accuracy are improved obviously. |