复杂转子系统支承阻尼优化设计

用拟模态综合法分析计算复杂转子系统的不平衡响应;以系统的不平衡响应和支承动载荷为目标函数,对支承阻尼进行了优化设计.通过对一双转子系统的分析计算,说明所提出的理论、方法对于旋转机械的动力特性设计和改进是有价值的.     

信息熵和判断矩阵的专家聚类赋权法

为了降低专家聚类赋权过程中由排序向量引起的不确定性和判断矩阵引起的矛盾性,提高权值分配的精确性,提出了基于信息熵和判断矩阵相结合的专家聚类赋权法。该方法采用聚类分析原理,对排序向量进行分类,根据分类结果、信息熵值和一致性比率确定专家权重系数。实例分析表明:基于信息熵和判断矩阵相结合的专家聚类赋权法在具体应用中得到的结果离期望值更近,说明该算法有效可行。     

Crane scheduling with spatial constraints

In this work, we examine port crane scheduling with spatial and separation constraints. Although common to most port operations, these constraints have not been previously studied. We assume that cranes cannot cross, there is a minimum distance between cranes and jobs cannot be done simultaneously. The objective is to find a crane‐to‐job matching which maximizes throughput under these constraints. We provide dynamic programming algorithms, a probabilistic tabu search, and a squeaky wheel optimization heuristic for solution. Experiments show the heuristics perform well compared with optimal solutions obtained by CPLEX for small scale instances where a squeaky wheel optimization with local search approach gives good results within short times. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004.     

基于空间平滑的单次快拍DOA估计方法

针对DOA估计的实时性和数据污染影响,给出了一种基于空间平滑的单次快拍DOA估计算法.由空间平滑技术,对接收的单次快拍数据采取解相干,再对Toeplitz矩阵进行协方差处理、采用特征分解、MUSIC算法和ESPRIT算法对信号实现DOA估计.该算法只需单次快拍,大大地减少了计算量,并且比现有的算法估计性能更好.采用计算机实验模拟分析和验证,证实了其有效性.     

铁电薄膜和铁电器件的发展及应用

论述了铁电体的基本原理和发展过程以及铁电体在商业上的潜在价值 .在采用纳米技术制备铁电薄膜成为现实后 ,铁电记忆就成为当今最热门的研究课题 .     

受压带肋圆柱壳体固有振动频率和稳定性计算

论述了丧失舱段总稳定性是潜艇耐压壳体在深潜时的主要破坏模式 .并将振动屈曲理论应用于潜艇耐压壳体稳定性的研究 ,在 Donell公式的基础上 ,导出了带肋圆柱壳体的整体固有振动频率与壳体所受外界水压之间的关系表达式 ,据此解出带肋圆柱壳体整体失稳的理论压力值 .最后 ,将公式的计算结果、实验结果和有限元法的计算结果进行比较 ,得出几点结论 .     

双速制声自导鱼雷主动开机时机研究

鱼雷主动声自导寻的信号是潜艇探测来袭鱼雷的主要信息源之一,主动声自导开机时机是鱼雷发射时需要设定的重要参数,它直接影响鱼雷攻击的隐蔽性。通过分析双速制鱼雷辐射噪声对潜艇鱼雷报警距离的影响,提出了一种双速制鱼雷直航搜索阶段的变速策略,在此基础上建立了鱼雷主动声自导开机时机解算模型,仿真结果表明,此方法简单高效,结论详实可信,对双速制鱼雷发射诸元解算具有一定的实用价值。     

Discrete repairable reliability systems

Consider a reliability system consisting of n components. The failures and the repair completions of the components can occur only at positive integer-valued times k ϵ N₊₊ ϵ (1, 2, …). At any time k ϵ N₊₊ each component can be in one of two states: up (i.e., working) or down (i.e., failed and in repair). The system state is also either up or down and it depends on the states of the components through a coherent structure function τ. In this article we formulate mathematically the above model and we derive some of its properties. In particular, we identify conditions under which the first failure times of two such systems can be stochastically ordered. A variety of special cases is used in order to illustrate the applications of the derived properties of the model. Some instances in which the times of first failure have the NBU (new better than used) property are pointed out. © 1993 John Wiley & Sons, Inc.     

模糊相似优先比法的坦克分队火力分配方案优选

火力分配是坦克分队火力运用的核心内容,而符合战场实际的火力分配方案是坦克分队火力发挥整体效益的关键.根据"消灭敌人、保存自己"的原则和作战实际需要,充分考虑了火力分配方案优选因素,用改进的层次分析法确定各因素权重,以减少主观判断的随意性,在此基础上,通过模糊相似优先比法建立了对各现存火力分配方案的优选模型,并提出了最佳方案的计算方法.最后通过实例,证明了该方法是有正确性和定用性.     

Dynamic pricing and matching in ride-hailing platforms

Ride-hailing platforms such as Uber, Lyft, and DiDi have achieved explosive growth and reshaped urban transportation. The theory and technologies behind these platforms have become one of the most active research topics in the fields of economics, operations research, computer science, and transportation engineering. In particular, advanced matching and dynamic pricing (DP) algorithms—the two key levers in ride-hailing—have received tremendous attention from the research community and are continuously being designed and implemented at industrial scales by ride-hailing platforms. We provide a review of matching and DP techniques in ride-hailing, and show that they are critical for providing an experience with low waiting time for both riders and drivers. Then we link the two levers together by studying a pool-matching mechanism called dynamic waiting (DW) that varies rider waiting and walking before dispatch, which is inspired by a recent carpooling product Express Pool from Uber. We show using data from Uber that by jointly optimizing DP and DW, price variability can be mitigated, while increasing capacity utilization, trip throughput, and welfare. We also highlight several key practical challenges and directions of future research from a practitioner's perspective.