ID 原文 译文
38666 仿真分析表明,当阵列天线存在幅相误差时,本文所提方法具有良好的超分辨DOA估计性能。 Simulation analysis shows that when the array antenna amplitude-phase error exists, this article proposed method has good super resolution DOA estimation performance.
38667 针对网络控制系统诱导时延具有的随机性、非平稳性、非线性等特点,提出了一种基于改进的集总平均经验模态分解(modified ensemble empirical mode decomposition,MEEMD)-排列熵和布谷鸟搜索(cuckoo search,CS)优化的小波神经网络(wavelet neural network,WNN)时延预测算法。 View of the induction time delay in networked control systems with random, non-stationary and nonlinear characteristics, puts forward a kind of based on improved lumped average empirical mode decomposition (modified ensemble empirical mode decomposition, MEEMD) - permutation entropy and cuckoo search (cuckoo search, CS) optimization of wavelet neural network (wavelet neural network, the WNN) time delay prediction algorithm.
38668 首先通过MEEMD对网络诱导时延序列进行处理,分别计算各模态的排列熵值,对复杂度相近的模态进行重组后得到新的子序列,从而达到降低建模复杂度和减少计算量的目的;然后利用CS算法优化的WNN预测新的子序列;最后叠加各子序列预测结果以获得时延序列的最终预测值。 First by MEEMD to deal with the network induced delay sequence, calculate the entropy of the modal, the complexity of similar modal new subsequence after restructuring, so as to reduce the purpose of modeling and reduce the computation complexity;Then use new subsequence CS algorithm of WNN forecast;Finally stack each subsequence predicted results in order to obtain the time delay sequence finally predicted.
38669 仿真表明,该算法具有较好的预测精度,能反映时延序列的总体趋势,可有效地降低异常值影响等优点。 Simulation shows that this algorithm has good prediction accuracy, could reflect the overall trend, delay sequence can effectively reduce the abnormal value influence, etc.
38670 为了提高不确定环境下无人机(unmanned aerial vehicle,UAV)对目标捕获能力,进而提高多UAV协同搜索效率,提出了基于双属性概率图结合改进的协同进化遗传算法(improved co-evolutionary genetic algorithm,ICEGA)的多UAV协同目标搜索方法。 In order to improve the uncertain environment UAV (unmanned aerial vehicle, UAV) to the target acquisition ability, thus improve the efficiency of multiple uavs cooperative search, based on the double attribute probability map combined with improved co-evolutionary genetic algorithm (improved co - evolutionary based algorithm, ICEGA) multiple uavs cooperative target search method.
38671 首先,根据环境的先验信息,在原概率图基础上引入标志位,建立基于双属性矩阵的待搜索环境概率模型,提高环境和目标的信息感知准确度; First of all, according to the environment of a priori information, flags, introduced on the basis of the original probability graph, set up the environment to search probability model based on dual attribute matrix, improve the environment and the target of information perception accuracy;
38672 其次,定义UAV的飞行规则并结合目标先验概率图信息,建立UAV运动模型及确定最大收益的目标函数; Second, the definition of the UAV flight rules and combining with the target prior probability graph information, establish UAV motion model and determine the maximum benefits of the objective function;
38673 最后,建立分布式UAV之间的信息交互模型,运用ICEGA算法优化产生最优协同决策输入航向角集合,在线实时滚动优化产生最优协同路径。 Finally, establish the information interaction between the distributed UAV model, using ICEGA algorithm produces the optimal coordinated decision input set course Angle, online real-time optimization to produce optimal path together.
38674 实验结果表明,基于双属性概率图结合ICEGA算法更能够保证最优路径的产生,使得UAV能够准确地搜索到目标;同时,对比仿真验证了ICEGA算法能够提高UAV之间的协同性,保证了路径可行性及提高了目标搜索效率。 By combining the experimental results show that based on the double attribute probability ICEGA algorithm is more able to ensure the production of the optimal path, the UAV can accurately search to the target;At the same time, the simulation verifies the ICEGA algorithm can improve the collaborative between UAV, guarantee the feasibility path and improves the search efficiency.
38675 未来空战将以中距空战为主,找出导致中距空战结果的原因是开展贴近实际的中距空战智能决策需解决的重要问题。 In the future war will be from the air combat is given priority to, find out the cause of distance in air combat result is in close to the actual distance in air combat intelligence decision-making important issues to be resolved.