Statistical inference on transit route‐level origin–destination flows using automatic passenger counter data

We consider inferring transit route‐level origin–destination (OD) flows using large amounts of automatic passenger counter (APC) boarding and alighting data based on a statistical formulation. One critical problem is that we need to enumerate the OD flow matrices that are consistent with the APC data for each bus trip to evaluate the model likelihood function. The OD enumeration problem has not been addressed satisfactorily in the literature. Thus, we propose a novel sampler to avoid the need to enumerate OD flow matrices by generating them recursively from the first alighting stop to the last stop of the bus route of interest. A Markov chain Monte Carlo (MCMC) method that incorporates the proposed sampler is developed to simulate the posterior distributions of the OD flows. Numerical investigations on an operational bus route under a realistic OD structure demonstrate the superiority of the proposed MCMC method over an existing MCMC method and a state‐of‐the‐practice method. Copyright © 2015 John Wiley & Sons, Ltd.     

公路养护决策模型研究

通过对多种公路养护决策模型的研究和分析,采用马尔可夫决策过程和动态规划理论建立决策模型,提高了模型的易用性和适用性,较好地解决了养护资金如何科学利用的问题,为公路养护管理部门提供决策参考依据。     

基于指数平滑法和马尔科夫模型的公路客运量预测方法

分析了常用的客运量预测方法,提出了一种新的基于指数平滑法和马尔科夫模型的公路客运量预测方法.基于公路客运量的实际值、线性拟合值与二次曲线拟合值,采用二次曲线拟合的方法计算了初始值与平滑系数.以安徽省2000～2009年相关数据为基础,应用指数平滑法预测了2010、2011年的公路客运量.以-11％、一5％、0、5％、11％为划分阈值,将指数平滑法预测结果的相对误差划分为4个状态区间,应用马尔科夫模型对指数平滑法的预测结果进行修正,并与模糊线性回归模型、指数平滑法的预测结果进行比较.分析结果表明:应用提出的方法,2010、2011年安徽省公路客运量的预测结果分别为14.209、15.712亿人,相对误差分别为1.195％、0.492％;应用指数平滑法,预测结果分别为13.468、14.893亿人,相对误差分别为-3.399％、-4.746％;应用模糊线性回归模型,预测结果分别为13.573、15.325亿人,相对误差分别为-2.647％、-1.983％.提出的方法精度较高,满足实际需求.     

道路交通事故的灰色马尔科夫预测模型与算法

将灰色模型与马尔科夫链结合,建立了针对道路交通事故预测的灰色马尔科夫模型.既可以发挥灰色系统预测精确的特点,又可以利用马尔科夫链对准确预测波动性数据的优势.在灰色马尔科夫链模型的算法基础上,进行灰色马尔科夫链预测系统的设计.用我国道路交通事故次数的数据进行预测验证.结果表明.灰色马尔科夫链模型能很大的提高预测的精度和效果,符合实际要求.     

Design and development of a stated choice experiment for interdependent agents: accounting for interactions between buyers and sellers of urban freight services

Stated choice experiments have proven to be a powerful tool in eliciting preferences across a broad range of choice settings. This paper outlines the elements of a group-based experiment designed for interdependent urban freight stakeholders, along with the procedure to administer the questionnaire sequentially. The focus is on the design of a computer-assisted personal survey instrument and the value in disseminating the details of a new approach to design and collect stated choice data for interacting agents. The paper also discusses how to specify a reference alternative, and then how to recruit appropriate real-market or representative decision-making group members to participate in a subsequent phase of the survey, which incorporates the reference alternative and contextual information from an initial phase. The empirical strategy, set out in some detail, provides a new framework within which to understand more fully the role that specific attributes, such as variable user charges, influencing freight distribution chains might play, and who in the supply chain is affected by specific attributes in terms of willingness to pay for the gains in distribution efficiency.

差分跳频图案性能检验探讨

差分跳频是一种新的扩展频谱通信技术,它主要归结于一种G函数算法。本文在介绍差分跳频基本原理的基础上,将差分跳频的频率跳变过程建模成齐次马尔可夫链。分析了G函数的功能,重点讨论了差分跳频图案性能的检验方法;将常规跳频图案的一维均匀性检验进行了扩充,同时建议采用不可约性、频隙滞留检验,其中频隙滞留是本文提出应用于差分跳频图案性能的检验。     

基于灰色预测-马尔可夫链-定性分析的铁路货运量预测

科学的货运量预测对铁路发展战略的制定具有十分重要的意义。分析以往对铁路货运量预测的相关文献及其预测精度,并分析影响预测精度的因素,定量分析与定性分析相结合有利于提高预测的准确性。采用灰色预测-马尔可夫链-定性分析相结合的方法对铁路货运量进行预测,经分析表明:灰色模型预测结果精确度受原始数据变化幅度的影响较大,通过马尔可夫链修正,预测结果得到较大改善;由GM(1,1)预测值及马尔可夫状态转移下的最大概率可知铁路货运量的发展趋势;"十一五"期间铁路货运量增长速度将放缓,但仍将保持较高的增长率。     

Multi-Point and Multi-Interval Availabilities for Markov Repairable Systems with History-Dependent Up and Down States

A Markov repairable system with history-dependent up and down states is presented. The state space of the repairable system is divided into three sets, which are up states, down states and changeable states.Using aggregated stochastic processes, we can get the multi-interval availability and multi-point availability for the Markov repairable system. Finally, numerical examples are given to illustrate the obtained results.     

基于 MCMC的导弹多阶段可靠性评估*

针对导弹在研制试验中存在多阶段、样本量小而造成传统评估误差大的问题,建立了基于模糊理论、Bayes方法和马尔可夫链蒙特卡罗法（MCMC）的可靠性评估模型。根据专家信息和模糊理论确定可靠性先验分布;并利用Bayes公式得到可靠度后验分布函数;结合试验多阶段的特点,通过 MCMC模型对不同阶段导弹的可靠性进行评估,其中利用Gibbs抽样算法对模型进行求解。通过算例分析,验证了模型的有效性,为可靠性增长评估提供了新的思路。