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981.
为降低鲁棒优化模型最优解的保守性,以最小化违约车辆数和总惩罚成本为目标,建立针对旅行时间不确定的开放式车辆路径问题的弱鲁棒优化模型。对于不确定数据集的每个取值,该模型的最优解可以使其目标函数值始终不超过某数值,进而改善最优解的保守性。为提高启发式算法发现最优解的概率,提出一种自设计遗传算法对模型进行求解,其主要思想是利用粒子群算法搜索出可使遗传算法预期产生最好解的算法要素,并将其进行组合,从而产生新的遗传算法。采用新产生的遗传算法对模型继续求解,输出最好解。计算结果表明:与以往的鲁棒优化方法相比,弱鲁棒优化方法的最优解的保守性显著降低。 相似文献
982.
全地形环境感知系统是研究车辆自主能力的重要部分,也是车辆安全行驶的绝对基础,而车辆的可通行区域分析则是环境感知系统中不可缺少的一步。本文分析了全地形环境下可能对装备车辆的地面通行性产生影响的众多地理环境因素,并结合多类型的地理环境因素,对包含地面坡度、植被、水系和建筑物等因素在内的,能够反映地面可通行性的车辆可通行区域以及装备车辆的可行驶区域进行规划。依托 ArcGIS平台和C++编程语言,对ArcGIS进行了二次开发,建立了一套针对全地形复杂环境下的路面可通行区域分析模型。该模型可以根据装备车辆的不同参数实现地理因子影响系数的设定,满足不同条件下车辆的可通行区域规划。 相似文献
983.
984.
985.
当前,地面无人装备作为多能合一的新质作战力量,已成为世界各军事强国发展的重点,对未来陆战形态影响深远。为准确把握地面无人装备对陆战的影响及未来陆战形态发展趋势,本文首先通过对地面无人装备的发展现状及在研项目的分析,分析装备能力的发展趋势以及可担负的作战任务;其次,从颠覆战场形态、改变作战方式及影响指挥控制方式三个方面阐述了地面无人装备给未来陆战带来的影响;再次,从无人化技术、作战样式及指挥决策三个方面对未来陆战形态的演进进行分析;最后为应对未来陆战变革带来的机遇与挑战,从军事需求、技术发展、优势保持及人才培养四个方面提出了对策与建议,具有一定的理论研究意义。 相似文献
986.
《防务技术》2020,16(4):811-824
For the automatic tracking of unknown moving targets on the ground, most of the commonly used methods involve circling above the target. With such a tracking mode, there is a moving laser spot on the target, which will bring trouble for cooperative manned helicopters. In this paper, we propose a new way of tracking, where an unmanned aerial vehicle (UAV) circles on one side of the tracked target. A circular path algorithm is developed for monitoring the relative position between the UAV and the target considering the real-time range and the bearing angle. This can determine the center of the new circular path if the predicted range between the UAV and the target does not meet the monitoring requirements. A transition path algorithm is presented for planning the transition path between circular paths that constrain the turning radius of the UAV. The transition path algorithm can generate waypoints that meet the flight ability. In this paper, we analyze the entire method and detail the scope of applications. We formulate an observation angle as an evaluation index. A series of simulations and evaluation index comparisons verify the effectiveness of the proposed algorithms. 相似文献
987.
《防务技术》2020,16(3):588-595
3D-Honeycombed CL-20 structures with low critical size of detonation have been fabricated successfully for intelligent weapon systems using a micro-flow direct ink writing (DIW) technology. The CL-20-based explosive ink for DIW technology was prepared by a two-component adhesive system with waterborne polyurethane (WPU) and ethyl cellulose (EC). Not only the preparation of the explosive ink but also the principle of DIW process have been investigated systematically. The explosive ink displayed strong shear-thinning behavior that permitted layer-by-layer deposition from a fine nozzle onto a substrate to produce complex shapes. The EC content was varied to alter the pore structure distribution and rheological behavior of ink samples after curing. The deposited explosive composite materials are of a honeycombed structure with high porosity, and the pore size distribution increases with the increase of EC content. No phase change was observed during the preparation process. Both WPU and EC show good compatibility with CL-20 particles. Apparently high activation energy was realized in the CL-20-based composite ink compared with that of the refined CL-20 due to the presence of non-energetic but stable WPU. The detonation performance of the composite materials can be precisely controlled by an adjustment in the content of binders. The 3D honeycombed CL-20 structures, which are fabricated by DIW technology, have a very small critical detonation size of less than 69 μm, as demonstrated by wedge shaped charge test. The ink can be used to create 3D structures with complex geometries not possible with traditional manufacturing techniques, which presents a bright future for the development of intelligent weapon systems. 相似文献
988.
989.
《防务技术》2020,16(1):263-273
Electronic warfare is a modern combat mode, in which predicting digital material consumption is a key for material requirements planning (MRP). In this paper, we introduce an insensitive loss function (ε) and propose a ε-SVR-based prediction approach. First, we quantify values of influencing factors of digital equipments in electronic warfare and a small-sample data on real consumption to form a real combat data set, and preprocess it to construct the sample space. Subsequently, we establish the ε-SVR-based prediction model based on “wartime influencing factors - material consumption” and perform model training. In case study, we give 8 historical battle events with battle damage data and predict 3 representative kinds of digital materials by using the proposed approach. The results illustrate its higher accuracy and more convenience compared with other current approaches. Taking data acquisition controller prediction as an example, our model has better prediction performance (RMSE = 0.575 7, MAPE (%) = 12.037 6 and R2 = 0.996 0) compared with BP neural network model (RMSE = 1.272 9, MAPE (%) = 23.577 5 and R2 = 0.980 3) and GM (1, 1) model (RMSE = 2.095 0, MAPE (%) = 24.188 0 and R2 = 0.946 6). The fact shows that the approach can be used to support decision-making for MRP in electronic warfare. 相似文献
990.
《防务技术》2020,16(3):617-626
The increasing threat of explosions on the battle field and the terrorist action requires the development of more effective blast resistance materials and structures. Curved structure can support the external loads effectively by virtue of their spatial curvature. In review of the excellent energy absorption property of auxetic structure, employing auxetic structure as core material in curved sandwich shows the potential to improve the protection performance. In this study, a novel cylindrical sandwich panel with double arrow auxetic (DAA) core was designed and the numerical model was built by ABAQUS. Due to the complexity of the structure, systematic parameter study and optimal design are conducted. Two cases of optimal design were considered, case1 focuses on reducing the deflection and mass of the structure, while case2 focuses on reducing the deflection and increasing the energy absorption per unit mass. Parameter study and optimal design were conducted based on Latin Hypercube Sampling (LHD) method, artificial neural networks (ANN) metamodel and the nondominated sorting genetic algorithm (NSGA-Ⅱ). The Pareto front was obtained and the cylindrical DAA structure performed much better than its equal solid panel in both blast resistance and energy absorption capacity. Optimization results can be used as a reference for different applications. 相似文献