道路通行能力不确定性分析方法研究

在分析通行能力不确定性及其产生的原因基础上,应用数理统计有关概念给出了通行能力不确定性度量方法.针对通行能力是估计值的特点,提出了应用自助法来分析通行能力的不确定性问题.最后,结合快速路基本路段通行能力的速度-流量统计分析模型,应用上述方法对快速路基本路段通行能力不确定性进行了分析.     

Uncertainty Quantification for Structural Optimal Design Based on Evidence Theory

Uncertainty design can take account of aleatory and epistemic uncertainty in optimal processes.Aleatory uncertainty and epistemic uncertainty can be expressed as evidence theory uniformly, and evidence theory is used to describe the uncertainty. Transferring and response with evidence theory for structural optimal design are introduced. The principle of response evaluation is also set up. Finally, the cantilever beam in a test system is optimized in the introduced optimization process, and the results are estimated by the evaluation principle. The optimal process is validated after the optimization of beam.     

计算网格对列车空气动力学不确定性的影响

为评价计算网格对明线列车空气动力学数值仿真计算结果的影响,基于计算流体力学,研究了计算网格对列车气动特性的不确定性. 首先根据3种不同尺寸的计算网格及其计算结果,提出了计算网格对列车气动力和表面压力不确定性的计算方法;其次以ICE2列车为研究对象,划分了3种不同尺寸的计算网格,数值仿真得到了列车气动力和典型截面的压力;最后研究了该列车头车气动力和典型截面压力的不确定性. 研究结果表明:数值仿真得到的气动侧力系数与试验数据的误差仅为0.31%;车身迎风侧表面压力的不确定性接近于0;车身表面压力不确定性较大的位置主要位于车体底部,其最大不确定度达到1.42;头车侧力系数的不确定度为0.002 6,而头车升力系数的不确定度为0.509 3.      

发动机性能试验比油耗测量结果的不确定度分析

通过介绍测量不确定度的基本知识,对发动机性能试验中比油耗测量结果标准不确定度的影响因素、分量计算、不确定度的建模及其评定、数据处理方法作一介绍,有望为同类试验测量结果中不确定度评定方案的确定和后续处理提供参考。     

不确定需求下轨道交通网络的鲁棒性优化

轨道交通网络设计是轨道交通规划的重点,本文研究不确定需求下轨道交通网络设计的鲁棒性优化问题.提出了不确定需求下轨道交通网络鲁棒性的概念.针对不确定需求可以被预测和不可以被预测的两种情况,分别建立了scenario 模型、minmax模型,这两个模型在优化目标中均综合考虑了最小化轨道交通线路总长度、最小化乘客总出行距离、最小化乘客总换乘次数,并基于遗传算法给出了这两个模型的求解算法.scenario 模型权衡网络的服务水平与网络对于不确定需求的抗干扰能力;minmax 模型侧重于网络在最坏情况下仍然能够保持较好的服务性能.最后,给出算例,验证了提出模型与算法的有效性.     

Numerical Simulation of Focused Wave and Its Uncertainty Analysis

On the basis of the transient water wave (TWW) theory, focused wave is generated in the circulating water channel. Numerical simulation of the focused wave is carried out by solving the Reynolds averaged Navier-Stokes (RANS) equations. The dynamic grid technique is adopted to simulate the motion of the wave maker, and the volume of fluid (VOF) method is used to capture the free surface of the wave. The simulation results are compared with the measured data, and good agreement is obtained. For quantitative estimation of the numerical simulation error and uncertainty, the uncertainty analysis method recommended by the International Towing Tank Conference (ITTC) procedure is performed for the simulation results of the surface elevations at different positions. Both grid-convergence and time-step-size convergence studies are conducted using three types of grids and time step sizes. The simulation results are all monotonously convergent in the verification procedure, and the validations of the simulated surface elevations with the positions at 3.5, 4.0 and 4.5m are all achieved by comparing with the validation uncertainty. It is found that the numerical simulation errors caused by the grid and time-step-size in the convergence studies have the same order of magnitude. In addition, the numerical errors and uncertainties for the surface elevations at different positions are compared and discussed in detail. This paper presents the first attempt to carry out the uncertainty analysis of the simulation of focused wave, and the effectiveness of the proposed verification and validation procedures in the uncertainty analysis is demonstrated.     

多元数据下的公交站点客流不确定性分析

利用长期收集的公交站点IC卡刷卡数据,基于区间不确定性理论,提出公交上下车站点区间不确定性客流推导方法.首先,将公交IC卡数据和GPS数据与公交站点信息相融合,确定IC卡刷卡的上车站点及其区间不确定性客流;然后,对公交刷卡行为进行分析,考虑乘客个体出行特征、乘客出行距离和站点吸引权重,提出下车站点客流推导概率模型及相应算法,通过区间数处理方法,得到下车站点客流区间值.最后,以2015年11月13日~12月25日深圳市21路公交为期6周的IC卡刷卡数据和GPS数据为例进行实例分析.     

基于分布式网络的分步滤波算法的改进

在实际的多传感器动态系统中,传感器之间网络通讯时要进行坐标转换,该过程具有的不确定性将对融合结果产生不利影响。文章对已有的基于分布式网络结构的分步式滤波算法进行了改进,考虑了这种不确定性产生的误差。在某一时刻所有传感器测量信息被获得后,先将这些测量信息进行坐标统一处理,再用中心坐标系统下的测量信息依次对先前的估计逐个进行滤波更新,最终得到该时刻的全局融合估计。文章通过计算机仿真说明了该算法的精确度不仅与集中式算法的精确度仍然相当,而且具有更实际的应用价值。     

公路网规划环境影响评价中的不确定性分析

公路网规划环境影响评价中的不确定主要来自公路网规划方案的不确定和环境信息的不确定。具有普遍性、传递性、累积性和可降低性,对决策者存在着较大的干扰,但是可以通过使用基于情景分析的预测方法、广泛开展公众参与以及通过多方协作的方式开展环境影响评价工作等方法来降低。     

Imprecise reliability assessment for heavy numerical control machine tools against small sample size problem

Small sample size problem is one of the main problems that heavy numerical control (NC) machine tools encounter in their reliability assessment. In order to deal with the small sample size problem, many indirect reliability data such as reliability data of similar products, expert opinion, and engineers’ experience are used in reliability assessment. However, the existing mathematical theories cannot simultaneously process the above reliability data of multiple types, and thus imprecise probability theory is introduced. Imprecise probability theory can simultaneously process multiple reliability data by quantifying multiple uncertainties (stochastic uncertainty, fuzzy uncertainty, epistemic uncertainty, etc.) together. Although imprecise probability theory has so many advantages, the existing natural extension models are complex and the computation result is imprecise. Therefore, they need some improvement for the better application of reliability engineering. This paper proposes an improved imprecise reliability assessment method by introducing empirical probability distributions to natural extension model, and the improved natural extension model is applied to the reliability assessment of heavy NC machine tool spindle to illustrate its effectiveness.     

基于GPGPU的快速医学图像FCM分割算法

由于医学图像生成容易受到空间时间影响,噪声较大,具有不确定性,传统的硬分割方法很难取得理想的分割结果.模糊分类技术能很好地处理医学图像中的不确定性,却由于计算量大不能保证实时性.灰度统计方法和通用计算图形处理器技术的引入,保证了初始聚类中心的准确性.又由于模糊C均值聚类算法是可并行的,将其改进并在图形处理器上完成计算,降低了算法迭代次数和计算时间,保证了实时性.实验结果表明,使用该方法对医学图像分割得到了良好的结果.     

考虑行程时间不确定性的服务设施时空可达性度量

在我国拥挤的多模式交通网络中,出行者的行程时间具有较大的不确定性.行程时间不确定性是影响人们出行行为选择的重要因素,对于某些重要活动(如就医等),人们对行程时间的可靠度有较高要求.本文以南京市玄武区综合医院的时空可达性为例,采用引力模型和行程时间预算模型深入探索多模式交通网络中服务设施的时空可达性,提出了考虑行程时间不确定性的时空可达性度量方法,针对不同交通模式分析了出行者的风险规避行为,为城市多模式交通规划和土地利用布局提供了有效依据及评价指标.研究表明,对于不同的交通模式,在不同可靠性下服务设施的时空可达性具有显著差异.     

高效电机效率测试方法的选取与分析

文章通过对112B法的计算方法以及不确定度原理的分析,并通过具体实验进行电机效率低不确定度的数值计算,从而得到比较符合实际的电机效率,对电机及系统的节能具有指导意义。     

确保水深模型航海安全性的深度保证率控制方法

针对当前海图水深应用在保证航海安全方面的不足, 提出了海图水深的深度保证率控制方法, 确保水深模型服务于航海的安全性。利用海图水深注记点, 建立不规则三角网水深模型表面, 推导了模型表面任意位置水深的整体计算公式。在考虑水深源数据不确定度对航海安全影响的基础上, 定量分析了水深模型在任意位置处描述不确定度的影响。通过在模型点上附加不确定度来控制描述不确定度的影响, 将水深模型的深度保证率控制在规定要求之内。在比例尺分别为1∶2 000、1∶5 000、1∶10 000、1∶50 000的海图上, 对提出的面控方法进行验证, 并与传统方法、点控方法进行了对比。分析结果表明: 与传统方法相比, 在4种海图上, 面控方法深度保证率的合格率分别提高了51.72%、49.37%、38.71%、28.39%;与点控方法相比, 面控方法分别提高了4.10%、5.00%、5.06%、9.65%;随着比例尺减小, 传统方法深度保证率的合格率有所提高, 点控方法有所下降, 而面控方法因为综合考虑了源数据不确定度和模型描述不确定度的影响, 深度保证率的合格率始终保持为100%;面控方法能将深度保证率控制在规定指标(97.5%)范围内, 而传统方法和点控方法均不能达到规定指标, 说明了面控方法的优越性。     

An Adaptive Sliding Mode Tracking Controller Using BP Neural Networks for a Class of Large-scale Nonlinear Systems

A new type controller, BP neural-networks-based sliding mode controller is developed for a class of large-scale nonlinear systems with unknown bounds of high-order interconnections in this paper. It is shown that decentralized BP neural networks are used to adaptively learn the uncertainty bounds of interconnected subsystems in the Lyapunov sense, and the outputs of the decentralized BP neural networks are then used as the parameters of the sliding mode controller to compensate for the effects of subsystems uncertainties. Using this scheme, not only strong robustness with respect to uncertainty dynamics and nonlinearities can be obtained, but also the output tracking error between the actual output of each subsystem and the corresponding desired reference output can asymptotically converge to zero. A simulation example is presented to support the validity of the proposed BP neural-networks-based sliding mode controller.     

不确定性对城市交通出行者路径选择的影响

为了研究城市交通中旅行时间的不确定性对出行者路径选择的影响, 基于展望理论, 提出了出行者规避不确定性假说, 应用贝叶斯模型分析了重复出行中出行者对不确定性的认知更新及其对出行行为的影响, 并通过调查数据进行了实例验证。分析结果表明: 77.73%的出行者偏好旅行时间不确定性小的路径; 路径旅行时间不确定性降低时, 有66.39%的出行者改变了出行时间, 平均时间预算减少了10.03%;对路径熟悉程度增加时, 有70.90%的出行者改变了出行时间, 平均时间预算减少了15.56%。可见, 出行者的出行时间预算随旅行时间不确定性的下降和重复出行的增加而减少。     

基于不确定理论的常规公交车辆调度优化

为提高公交车的利用效率,本文将公交车辆调度方案划分为高峰型和平峰型。在考虑乘 客候车时间与站间运行时间不确定的现实条件下,综合考虑不同车型的运营成本和乘客候车成 本;基于不确定理论建立混合车型下的双重不确定多目标规划模型,并通过遗传算法的python编 码求解。以南昌市211路公交上行为例,进行sumo仿真结果表明：在保证公交持续运营的前提 下,调整车辆调度方案有助于降低成本和提高运行效率;在高峰期,将发车间隔降低25%,公交车 统一使用纯电动客车,总成本降低5%,平均延误减少4%;平峰期,总成本降低10%,平均延误降 低3%。两组仿真结果发现,考虑不确定因素的公交车辆合理调度安排有利于充分利用公交车辆 资源和提高运行效率。     

Bayesian Network Based Approach for Diagnosis of Modified Sequencing Batch Reactor

Wastewater treatment is a complicated dynamic process affected by microbial, chemical and physical factors. Faults are inevitable during the operation of modified sequencing batch reactors(MSBRs) because of the uncertainty of various factors. Abnormal MSBR results require fault diagnosis to determine the cause of failure and implement appropriate measures to adjust system operations. Bayesian network(BN) is a powerful knowledge representation tool that deals explicitly with uncertainty. A BN-based approach to diagnosing wastewater treatment systems based on MSBR is developed in this study. The network is constructed using the knowledge derived from literature and elicited from experts, and it is parametrized using independent data from a pilot test.A one-year pilot study is conducted to verify the diagnostic analysis. The proposed model is reasonable, and the diagnosis results are accurate. This approach can be applied with minimal modifications to other types of wastewater treatment plants.     

μ—Syntheses of Suspension Systems for EMS and EDS Maglev Vehicles

Introduction　　Currently ,therearetwokindsoftechnologiesforMaglevvehiclesoftenused .Oneiselectromagneticsystem (EMS) ,inwhichthevehicleislevitatedthroughtheattractiveforcesproducedbyelectromagnets.Anotheriselectrodynamicssystem (EDS) ,inwhichthevehicleis…     

需求不确定的枢纽辐射式航线网络设计

为了使枢纽辐射式航线网络能够适应不确定的交通需求, 分析了航空运输需求不确定的影响因素及长短距离交通需求分布特性, 提出需求不确定有容量限制的枢纽辐射式航线网络设计模型, 并将其转化为机会约束规划模型, 采用基于随机模拟的遗传算法对模型进行求解。以包含15个城市的中国航线网络规划为例, 进行了需求不确定情况下的枢纽辐射式航线网络设计。研究结果表明: 在合理的枢纽数量范围内, 需求确定与不确定的枢纽辐射式航线网络选址结果基本相同, 但与长距离交通出行相比, 短距离路径选择变化较大; 需求不确定的枢纽辐射式网络最小运输成本较低, 并更能真实地反映网络性能。