基于MCTS-HM的重型汽车多参数运行工况高效构建方法

提出了一种基于蒙特卡洛树搜索 （Monte Carlo Tree Search,MCTS） 和启发式方法 （Heuristic Method, HM）的多参数运行工况高效构建方法。根据工况质量要求,选取表征行驶工况特征的速度、加速度和坡度参数相关指标,设计工况的目标函数;改进多个启发式方法,确保被作用后的工况序列仍可满足行驶工况动态转移特性;采用MCTS选择更适合的启发式方法,进而高效地收敛至多参数目标行驶工况。基于重型汽车实际采集的试验数据,多次分析结果表明,生成的多参数行驶工况所有特征指标相对偏差均可保持在设定阈值以内,表明生成工况与原始数据特征具备一致性;相比于纯随机启发式方法,该方法能快速构建多参数期望运行工况。     

无缝线路稳定性可靠度计算及参数敏感性分析

随着我国铁路提速进程的推进,对轨道平顺性的要求日益提高,有砟轨道无缝线路稳定性的研究就显得更加重要。无缝线路稳定性的设计参数（道床横向阻力、轨道原始弯曲、钢轨温升幅度、扣件阻矩系数）具有明显的随机性,运用概率方法对无缝线路稳定性进行分析是十分必要的。本文基于蒙特卡洛方法,分析无缝线路稳定性可靠度,并且采用单参数敏感性分析法,通过改变各参数的平均值,而保持其变异系数不变,对设计参数进行敏感性分析。结果表明,设计参数中的道床横向阻力、轨道原始弯曲、钢轨温升幅度对于无缝线路稳定性可靠度具有较高的敏感性,而扣件阻矩系数对可靠度的影响较小。并且得出一些对于保障行车安全和提高线路养护维修的效益有一定参考价值的结论。     

蒙特卡罗方法、核模拟程序MCNP及MCNP在核测井中的应用

主要介绍了蒙特卡罗方法的原理及应用,蒙特卡罗超级模拟程序MCNP及其MCNP在核测井中的应用,通过展示部分模拟测井的结果,揭示了MCNP在核测井数值模拟中的有效性和广泛用途.     

Stochastic Monte Carlo simulations of the pantograph–catenary dynamic interaction to allow for uncertainties introduced during catenary installation

The simulation of the pantograph–catenary dynamic interaction is at present mainly based on deterministic approaches. However, any errors made during the catenary stringing process are sources of variability that can affect the dynamic performance of the system. In this paper, we analyse the influence of dropper length, dropper spacing and support height errors on the current collection quality by applying a classic Monte Carlo method to obtain the probability density functions of several output quantities. The effects of installation errors are also studied for a range of train speeds. Finally, the pre-sag that, on average, produces the best behaviour of the system is identified, allowing for the uncertainty in the catenary installation. The results obtained show the convenience to consider variability in pantograph–catenary dynamic simulations.     

卡尔曼/粒子滤波器在船用组合导航中的应用

采用将全球定位系统GPS（Global Positioning System）与捷联惯性导航系统SINS（Strapdown Inertial Navigation System）进行组合导航的方式,组合后系统性能将优于GPS或SINS单独使用时的任一系统。介绍了基本粒子滤波器算法原理并对卡尔曼/粒子组合滤波器在船用GPS/SINS组合导航中的实现形式及算法特点进行了研究。仿真结果表明,对于船用SINS/GPS组合导航问题,卡尔曼/粒子组合滤波器能够获得较高的滤波精度,满足实际船用导航要求。     

Evaluation of simulation uncertainty in accident reconstruction via combining Response Surface Methodology and Monte Carlo Method

This paper focuses on the uncertainty of simulation results in accident reconstruction. Since the Monte Carlo Method (MCM) requires a large number of simulation runs, in order to reduce the simulation time of MCM in evaluating the uncertainty of simulation results, a new method named “Response Surface-Monte Carlo Method (RS-MCM)” was proposed. Firstly, Response Surface Methodology (RSM) was used to obtain an approximate model of the true accident simulation model, and then the uncertainty of simulation results was evaluated by combining this approximate model and MCM. The steps of RS-MCM include the generation of sample sets, the determination of response surface model and the statistical analysis of simulation results. The distribution of reconstruction results was obtained using RS-MCM, which can provide more comprehensive information in traffic accident survey, such as the probability of a simulation result at any given confidence interval falling within an arbitrary interval and so on. Finally, three cases have been employed to evaluate the effectiveness of the proposed RS-MCM.     

Network-based real option models

Building on earlier work to incorporate real option methodologies into network modeling, two models are proposed. The first is the network option design problem, which maximizes the expanded net present value of a network investment as a function of network design variables with the option to defer the committed design investment. The problem is shown to be a generalized version of the network design problem and the multi-period network design problem. A heuristic based on radial basis functions is used to solve the problem for continuous link expansion with congestion effects. The second model is a link investment deferral option set, which decomposes the network investment deferral option into individual, interacting link or project investments. This model is a project selection problem under uncertainty, where each link or project can be deferred such that the expanded net present value is maximized. The option is defined in such a way that a lower bound can be solved using an exact method based on multi-option least squares Monte Carlo simulation. Numerical tests are conducted with the classical Sioux Falls network and compared to earlier published results.     

基于Monte Carlo法的多车道公路桥梁车流模拟

在分析实测车辆数据的基础上,确定了模型车辆、车重、车头时距等交通特征的分布类型及参数.采用Monte Carlo法进行随机抽样,自编MATLAB程序,对自由车流进行模拟,得到车重、轴重在桥梁上的纵横向分布及其随时间变化情况;讨论了车辆占用车道不均匀系数的3种不同情况,发现轴重在桥上均呈多峰分布,峰值相近,但出现频率差异...     

蒙特卡洛法在滑坡稳定性可靠度分析中的应用

通过分析滑坡稳定性分析中存在的问题,考虑滑坡岩土体的不确定因素,从概率的角度对影响滑坡稳定的各种参数的不确定性进行定量分析,从而得到坡体稳定的不确定性。采用蒙特卡洛法针对一工程实例进行了计算分析,得到了在不同工况下滑坡失稳的概率值,计算结果验证了方法的合理性和可行性。     

Ising动力系统模拟收益率的多重分形分析

应用Ising模型和平均场理论构造符合股市收益率的动力系统,借助于计算机软件Mat-lab,利用蒙特卡洛模拟方法,通过调整参数模拟得出动力系统的收益率序列.分析发现：Ising动力系统构造的收益率同证券市场股票指数波动率一样具有厚尾等统计特征.对模拟收益率原序列和混洗后的序列进行多重分形分析,得出了模拟收益率序列存在分布多重分形和相关性多重分形的结论.