联合作战的远程火力战法动态分析方法*

用定量动态分析方法开发远程火力战法是联合作战规划中必须解决的重要问题。借助仿真和博弈分析的混合方法,在对博弈效用函数计算的基础上,构建基于识别真目标、假目标以及火力命中目标概率的二人非零和(TPNZS)非合作博弈模型来开发远程火力战法动态分析方法,对两个典型的联合作战远程火力打击战法性能的初步动态分析表明:战场势态的动态变化直接影响定量规划最优战法的结果。     

基于二次繁殖的自适应差分演化算法

分析了差分演化算法的基本原理，针对基本差分演化算法对控制参数选择敏感性强、算法后期收敛速度较慢等问题，提出了基于二次繁殖的自适应差分演化算法，并通过实验对改进算法的性能进行测试。实验结果表明，改进算法的性能优于基本差分演化算法和自适应差分演化算法。     

Revenue management under randomly evolving economic conditions

We consider a dynamic pricing model in which the instantaneous rate of the demand arrival process is dependent on not only the current price charged by the concerned firm, but also the present state of the world. While reflecting the current economic condition, the state evolves in a Markovian fashion. This model represents the real‐life situation in which the sales season is relatively long compared to the fast pace at which the outside environment changes. We establish the value of being better informed on the state of the world. When reasonable monotonicity conditions are met, we show that better present economic conditions will lead to higher prices. Our computational study is partially calibrated with real data. It demonstrates that the benefit of heeding varying economic conditions is on par with the value of embracing randomness in the demand process. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 66:73–89,2019     

基于SFS的磨粒图像三维重构

研究了一种由磨粒灰度图像直接恢复出磨粒图像三维信息的磨粒三维形貌恢复方法，以几种典型的磨粒灰度图像进行算法验证，实验结果表明，该方法简单，易于实现，恢复后的磨粒三维图像有较强的立体感。在不增加硬件成本的基础上，可以为磨粒的分析提供三维数据，为磨粒图像三维特征的提取奠定基础，对磨粒识别精度的提高产生重要的影响。     

多约束下的高超声速飞行器三维非线性自适应末制导律

面向多约束下高超声速飞行器末制导过程中的通道耦合、参数扰动、模型失配等突出问题,设计一种适于高超声速飞行器的三维非线性自适应末制导律。为了模型描述的完整性和简洁性,引入视线旋量和旋量速度的概念,并基于此建立三维制导参考模型和实际系统的表达式;为了保证制导律的鲁棒性和自适应性,基于自适应控制理论,设计一种三维非线性自适应制导律;通过数学推导证明了该制导律的稳定性。该制导律能够从理论上克服高超声速飞行器末制导面临的通道耦合、参数扰动、模型失配等突出问题,满足多约束制导要求。仿真结果验证了所设计制导律的有效性。     

基于深度神经网络的无线覆盖预测算法*

为保证新一代移动无线网络能够根据实时覆盖情况动态地调节小区天线参数，需要实现高效且准确的无线覆盖预测。传统的求解方法通过精确的场强预测来判断天线参数的优劣，虽然精度很高但需要大量的计算资源，无法满足5G和后5G移动网络通过实时覆盖预测进行射频参数动态调整的实际需求。现采用基于深度神经网络的算法对给定天线参数的覆盖效果进行预测，以取代对目标区域的精确场强预测。数值结果表明，该方法能够在保持计算准确性的同时显著减少计算量，为5G动态网络规划提供基础性参考数据。     

提高负重轮橡胶动态性能的研究

介绍了提高负重轮橡胶动态性能的研制情况,在传统的胎面胶配方基础上,通过试验确定主体生胶类型,通过调节补强填充体系和硫化体系的不同,研究混炼胶的物理性能和动态性能。结果表明,采用软、硬质炭黑并用的胎面胶,其力学性能可满足使用要求,定伸应力和抗疲劳性能有较大提高,动态生热明显降低,耐老化性能也有较大提高。     

基于门限的无线传感器网络密钥管理方案

由于无线传感器网络在能量消耗、内存开销和计算能力等方面的局限性，传统的网络密钥管理方法已不适用。为此提出了一种适用于无线传感器网络的密钥预分配方法——基于（t，n）-门限方案，给出了密钥分配方法，并从方案的连通性、安全性等方面进行了有效的分析，结果表明该算法在这些方面有一定的优势。     

虚拟环境下某型迫击炮自动机故障预测仿真分析研究

在对某迫击炮自动机的结构组成和机构动作分析的基础上,应用ADAMS软件建立了该武器自动机的虚拟样机模型,并结合实验数据和理论数据对自动机连发射击仿真结果的对比,验证了虚拟样机的正确性。以虚拟样机为工具,对自动机常见故障的影响因素进行了仿真分析和计算,为该武器的故障预测提供了理论依据和数据支持。     

Balancing a one‐way corridor capacity and safety‐oriented reliability: A stochastic optimization approach for metro train timetabling

In urban rail transit systems of large cities, the headway and following distance of successive trains have been compressed as much as possible to enhance the corridor capacity to satisfy extremely high passenger demand during peak hours. To prevent train collisions and ensure the safety of trains, a safe following distance of trains must be maintained. However, this requirement is subject to a series of complex factors, such as the uncertain train braking performance, train communication delay, and driver reaction time. In this paper, we propose a unified mathematical framework to analyze the safety‐oriented reliability of metro train timetables with different corridor capacities, that is, the train traffic density, and determine the most reliable train timetable for metro lines in an uncertain environment. By employing a space‐time network representation in the formulations, the reliability‐based train timetabling problem is formulated as a nonlinear stochastic programming model, in which we use 0‐1 variables to denote the time‐dependent velocity and position of all involved trains. Several reformulation techniques are developed to obtain an equivalent mixed integer programming model with quadratic constraints (MIQCP) that can be solved to optimality by some commercial solvers. To improve the computational efficiency of the MIQCP model, we develop a dual decomposition solution framework that decomposes the primal problem into several sets of subproblems by dualizing the coupling constraints across different samples. An exact dynamic programming combined with search space reduction strategies is also developed to solve the exact optimal solutions of these subproblems. Two sets of numerical experiments, which involve a relatively small‐scale case and a real‐world instance based on the operation data of the Beijing subway Changping Line are implemented to verify the effectiveness of the proposed approaches.