ID	原文	译文
7394	在没有新息加入的条件下,依次选取现有HFS隶属度可能值的均值作为一个新的延拓隶属度,直至所有HFS隶属度个数相等为止,并基于有序加权平均(ordered weighted averaging,OWA)算子归纳隶属度统一方法。	Under the condition of no new interest to join, in order to select the existing HFS membership degree of possible values for the mean as a new continuation membership, until all the HFS membership number is equal, and based on ordered weighted averaging (ordered weighted averaging,, OWA) operator inductive membership unified method.
7395	最后将所提出的方法应用到多传感器电子侦察情报的多属性决策问题中,基于改进的逼近理想解(technique for order preferences by similarity to ideal solution,TOPSIS-ε)法对各信源HFS属性判决进行多属性决策。	Finally the proposed method is applied to multi-sensor electronic reconnaissance information of multiple attribute decision making problems, based on improved close to ideal solution (technique for order preferences by similarity to ideal solution, TOPSIS - epsilon) method for each source HFS attribute decision for multiple attribute decision making.
7396	仿真试验分析了距离、距离参数、属性权重对决策结果的影响,并详细对比和验证了新方法在HFS隶属度NE方面的稳定性和直观性。	Simulation test distance, the distance parameter is analyzed, the influence of the attribute weights are the result of the decision, and compared in detail, and verified the new method in the aspect of HFS membership NE stability and intuitive.
7397	传统的湍流探测方法需要利用经验公式和参数化模型等,公式与模型的正确性大大影响了探测的准确性。	Turbulence in the traditional detection methods need to use parameterized model and empirical formulas, the correctness of the formula and model greatly influence the accuracy of detection.
7398	基于反向传播(back propagation,BP)神经网络多类分类方法的气象湍流目标探测算法无需借助经验公式和参数化模型,利用神经网络的分类功能,仅通过对大量数据的学习可有效地确立雷达回波与湍流强度之间的关系。	Based on back propagation (BP) back propagation, neural network classification method more weather turbulent target detection algorithms without the empirical formula and the parameterized model, neural network classification function, only through the study of a large amount of data can be effectively established the relationship between the radar echo and turbulence intensity.
7399	仿真结果表明,所提出的方法在进行湍流强度时有可忽略、轻微、中度、强4个等级分类,有良好的准确性,在进行湍流2个等级分类,即判定湍流有无时,准确率将大大提高。	The simulation results show that the proposed method in the turbulent intensity are negligible, mild, moderate, strong four grade classification, has a good accuracy, the turbulent two level classification, namely determine turbulent time, will greatly improve the accuracy.
7400	理论和实践结果表明,所提出的方法可以有效地进行湍流目标探测。	The theory and practice results show that the proposed method can effectively turbulence target detection.
7401	对地面运动目标的搜索是无人机(unmanned aerial vehicle,UAV)航路规划的重要研究内容之一,受目标运动的影响,传统的垂线扫描搜索方法对速度较大的运动目标搜索能力不足。	Search for ground moving target is UAV (unmanned aerial vehicle, UAV) one of the important research contents of route planning, the influence of the target motion, the traditional vertical scan search method for speed large moving target search ability is insufficient.
7402	为了提升对运动目标的搜索效率,提出多无人机(multi-unmanned aerial vehicle,multi-UAV)并排回寻式搜索方法,以回寻速度与推进距离为参数构建了协同搜索数学模型，搜索效率须在搜索速率和发现概率2个指标之间权衡,通过对模型参数进行优化,得出不同应用场景下的最优搜索方案。	Of moving targets in order to enhance the search efficiency, this paper puts forward multiple unmanned aerial vehicle (UAV) (multi - unmanned aerial vehicle, multi - UAV) back to search search method, side by side to find back speed and promote the distance as a parameter to build the mathematical model of collaborative search search efficiency in the search speed and detection probability trade-off between two indexes, through parameter optimization of the model, it is concluded that the optimal search scheme under different scenarios.
7403	仿真结果表明:与垂线扫描搜索法相比,在相同的发现概率下,该方法允许目标的运动速度更快;	Simulation results show that compared with the vertical scanning search method, under the same detection probability, this approach allows the target's movement speed faster;