ID 原文 译文
9274 首先描述了分布式兵力组织的组成要素,对规划问题进行了建模,并且提出了平台定价模型。 ‭First describes the distributed forces group elements, the modeling problem of planning, and platform pricing model is put forward.
9275 然后设计了一个分布式的协作框架,用来实现任务计划的动态调整,该框架由两个模块构成,第一部分是内部模块,该模块包括一个N-best算法和一个反馈策略,完成决策实体内部的二次分配; ‭And then designed a distributed collaborative framework, is used to implement the dynamic adjustment of mission planning, the framework consists of two modules, the first part is the internal module, the module includes a N - best algorithm and a feedback strategy, complete decision-making entities within the secondary distribution;
9276 第二部分是外部模块,当任务精度低于期望值时调用此模块,实现决策实体间的协作。 The second part is an external module, when the task accuracy well below expectations calls when the module, implementation decisions collaboration of the entity. ‭
9277 最后通过仿真实验证明了该模型的有效性,并讨论了模型在不同情况下的适用性。 Finally, simulation experiments prove the effectiveness of the proposed model, and discusses the applicability of the model under different circumstances.
9278 为将烟花算法应用于离散优化领域并有效求解多维背包问题,构建一种二进制反向学习烟花算法。 For fireworks algorithm was applied to discrete optimization areas and effectively solve the multidimensional knapsack problem, build a binary reverse learning algorithm of fireworks.
9279 首先,通过定义二进制字符串距离、二进制转置算子将烟花算法的爆炸算子、变异算子离散化,构建二进制烟花算法; ‭ First, by defining a binary string distance, binary transposed operator will explode fireworks algorithm operator, mutation operator discretization, build binary fireworks algorithm;
9280 其次,设计不完全二进制反向算子并证明其收敛性,构建二进制反向学习烟花算法; ‭Secondly, the design is not completely binary reverse operators and prove their convergence, build binary reverse learning algorithm of fireworks;
9281 ‭最后,对10个多维背包问题典型算例进行仿真分析并与多种智能优化算法进行对比分析。 ‭Finally, 10 multidimensional knapsack problem of typical example simulation analysis and comparative analysis with a variety of intelligent optimization algorithms.
9282 仿真实验结果表明,二进制反向学习烟花算法在求解多维背包问题时具有良好的收敛效率、较高的寻优精度和很好的鲁棒性。 Simulation experimental results show that the binary fireworks reverse learning algorithm in solving the multidimensional knapsack problem has good convergence optimization efficiency, high precision and good robustness.
9283 提出了一种通用的合成孔径雷达（synthetic aperture radar,SAR）系统分辨能力评估方法,该方法可对复杂轨迹SAR系统（比如圆轨迹,同步轨道卫星和双基地SAR等）的分辨能力进行高效率、高精度评估。 Put forward a general synthetic aperture radar (synthetic aperture radar, SAR) system resolution evaluation method, the method of complex trajectory SAR system (such as circular trajectory, synchronous orbit satellite, and bistatic SAR, etc. ‭) the resolving power of high efficiency, high precision evaluation.