一类具有校正隔离率随机SIQS模型的绝灭性与分布

该文探讨了一类具有校正隔离率的随机传染病模型,得到了该模型存在唯一的全局解.研究表明,当白噪声强度取较大值时,随机模型的解在无病平衡点附近是绝灭的,感染者的密度将指数衰减到零.当白噪声的强度较小时,随机模型的正解在地方病平衡点附近服从唯一的平稳分布.进而,若地方病平衡点是稳定的,在适当的条件下,该解渐近服从一个三维正态分布,且得到了均值与方差的表达式.最后,数值模拟图显示了该解的性质并对模型做出了合理的解释.     

综合广义预测自校正控制器的稳定性与随机收敛性

本文给出了广义预测自校正控制器的统一模式,证明了该控制器的闭环稳定性与随机收敛性。     

非线性回归模型校正和应用

本文提出了非线性回归模型的校正模型，该方法尤其适于当社会经济系统发生变化时供建立预测模型之用，从而扩大了非线性回归模型的应用范围。经实例验证，该方法的效果是显著的。     

带随机参数的AACD模型及其几何遍历性(英文)

在本论文中提出了一类新的AACD模型—带随机参数的AACD模型.带随机参数的AACD模型是AACD模型的拓展,该模型能更好的模拟实际情况,有更广泛的应用领域.并且给出该模型的转移概率,通过转移概率,得到了该模型的一系列概率性质.     

随机环境中随机指标分枝过程矩的渐近性

引入了随机环境中随机指标分枝过程模型,证明了该模型矩的渐近性。     

双随机环境下一维选举模型生存概率界的估计

本文用随机环境中随机游动的知识讨论了双随机环境中一维选举模型 ,给出了该模型生存概率界的估计 .     

基于声矢量水听器阵列误差的自校正算法

对声矢量水听器阵列的各类误差进行了分类,推导了各类误差对阵列信号模型的影响因子,通过Monte Carlo实验分析对比了各类误差对阵列DOA估计性能的影响,然后将方向性误差和位置误差归结为幅度误差和相位误差,在传统声压阵列误差校正模型和算法的基础上,得到矢量阵列误差自校正的优化模型及自校正算法,最后,通过仿真实验和外场实验的数据处理表明,自校正算法具有良好的参数估计性能,具有一定的工程实用性.     

基于随机参照点的均值-风险分析

本文依据参照依赖偏好模型提出了基于随机参照点的风险度量方法,进而构建了均值-风险模型,并讨论了该决策方法与随机占优之间的一致性。研究发现,该决策方法不仅与一级随机占优是一致的而且与二级随机占优也是一致的。由于二级随机占优与期望效用理论的一致性,因而所构建的均值-风险模型与期望效用理论也是一致的。     

跳台跳水的物理模型分析和体型修正

通过建立Euler-Poinsot刚体运动模型,模拟人体在跳台跳水时的运动情况.并且在此基础上建立左右非对称和前后非对称的运动模型,用于模拟复杂的转体跳水和屈体抱膝跳水.运动刚体模型详述了旋运动的动力学原理并导出各物理参数之间定量关系,能够求解模型得出运动员完成各个跳水动作的时间,进而得出该时间与运动员体型(身高,体重)之间的关系.随后设置了体型扰动因子,解析与身高、体重及体型扰动因子有关的体型校正系数,求解了体型校正公式用于所有跳水动作难度系数的修正.通过与现有的难度系数打分规则对比,模型不仅真实有效,还在部分动作上更具有公平性.     

基于BP的随机混合生产前沿面模型

本文提出了基于BP神经网络的随机混合生产前沿面(BP＿SHPF)模型，能够实现决策单元在不确定生产前沿面上的效率估计，并将其扩展应用到多投入多产出生产集合。利用蒙特卡洛模拟实验验证BP＿SHPF模型的有效性，再利用Spearman秩相关分析验证BP＿SHPF模型决策单元效率与原始DEA模型决策单元效率的相关性，并将BP＿SHPF模型应用于107家农村商业银行的生产效率估计，结果表明BP＿SHPF模型能够校正确定性生产前沿面并生成有效的效率排序。     

An improved seasonal rolling grey forecasting model using a cycle truncation accumulated generating operation for traffic flow

Accurate real-time prediction of urban traffic flows is one of the most important problems in traffic management and control optimization research. Short-term traffic flow has complex stochastic and nonlinear characteristics, and it shows a similar seasonality within intraday and weekly trends. Based on these properties, we propose an improved binding cycle truncation accumulated generating operation seasonal grey rolling forecasting model. In the new model, the traffic flow sequence of seasonal fluctuation is converted to a flat sequence using the cycle truncation accumulated generating operation. Then, grey modeling of the cycle truncation accumulated generating operation sequence weakens the stochastic disturbances and highlights the intrinsic grey exponential law after the sequence is accumulated. Finally, rolling forecasts of the limited data reflect the new information priority and timeliness of the grey prediction. Two numerical traffic flow examples from China and Canada, including four groups at different time intervals (1 h, 15 min, 10 min, and 5 min), are used to verify the performance of the new model under different traffic flow conditions. The prediction results show that the model has good adaptability and stability and can effectively predict the seasonal variations in traffic flow. In 15 or 10 min traffic flow forecasts, the proposed model shows better performance than the autoregressive moving average model, wavelet neural network model and seasonal discrete grey forecasting model.     

Modeling phase diagrams as stochastic processes with application in vehicular traffic flow

Motivated by the similarity between the fundamental diagram of vehicular traffic and the Maxwell–Boltzmann distribution of ideal gases, this paper proposed a methodology to model the fundamental diagram as a stochastic process which also applies to other real-world systems with similar nature. A concrete example is provided to illustrate the application of the methodology where the fundamental diagram of vehicular traffic is modeled as a stochastic process to capture the scattering effect in flow–density relationship. A verification study was conducted on the model using empirical data and the statistical analysis shows that the overall quality of the fitted stochastic process is acceptable. Related existing efforts are referenced to the proposed stochastic fundamental diagram where their similarities and differences are elaborated. Further discussion is carried out on the significance of the stochastic fundamental diagram as well as the proposed methodology with an additional real-world example to illustrate its applications.     

Some consequences of estimating parameters for the M/M/1 queue

An important interface between stochastic models and actual systems comes in estimating values for model parameters using “real world” data. This interface between models and systems is studied for one of the most elementary stochastic systems, the M/M/1 queue. Estimating arrival rates and service rates results in a notable discrepancy between the state distribution for the model (estimated parameters) and the state distribution for the actual system (known parameters). Also, the expected number of customers in the model is infinite regardless of the (unknown) value of the actual traffic intensity. The truth of this assertion is obvious if one allows estimated traffic intensities to equal or exceed one. However, it is shown that the mean for the model is infinite even if the estimated traffic intensity is restricted to be strictly less than one.     

A meta-model for multiobjective routing in MPLS networks

MPLS (Multiprotocol Label Switching) enables the utilisation of explicit routes and other advanced routing mechanisms in multiservice packet networks, capable of dealing with multiple and heterogeneous QoS (Quality of Service) parameters. Firstly the paper presents a discussion of conceptual and methodological issues raised by multiobjective routing optimisation models for MPLS networks. The major contribution is the proposal of a multiobjective routing optimisation framework for MPLS networks. The major features of this modelling framework are: the formulation of a three-level hierarchical routing optimisation problem including network and service performance objectives, the inclusion of fairness objectives in the different levels of optimisation and a two-level stochastic representation of the traffic in the network (traffic flow and packet stream levels). A variant of the general model for two classes of traffic flows, QoS traffic and Best Effort traffic, is also presented. Finally a stochastic teletraffic modelling approach, underlying the optimisation model, is fully described. Work partially supported by programme POSI of the III EC programme cosponsored by FEDER and national funds.     

Doubly uncertain transportation network: Degradable capacity and stochastic demand

This study developed a methodology to model doubly uncertain transportation network with stochastic link capacity degradation and stochastic demand. We consider that the total travel demand comprises of two parts, infrequent travelers and commuters. The traffic volume of infrequent travelers is stochastic, which adds to the network traffic in a random manner based on fixed route choice proportions. On the other hand, the traffic volume of commuters is stable or deterministic. Commuters acquire the network travel time variability from past experiences, factor them into their route choice considerations, and settle into a long-term habitual route choice equilibrium in which they have no incentive of switching away. To define this equilibrium, we introduce the notion of “travel time budget” to relate commuters’ risk aversion on route choices in the presence of travel time variability. The travel time budget varies among commuters according to their degrees of risk aversion and requirements on punctual arrivals. We then developed a mixed-equilibrium formulation to capture these stochastic considerations and illustrated its properties through some numerical studies.     

Two-stage stochastic variational inequalities: an ERM-solution procedure

We propose a two-stage stochastic variational inequality model to deal with random variables in variational inequalities, and formulate this model as a two-stage stochastic programming with recourse by using an expected residual minimization solution procedure. The solvability, differentiability and convexity of the two-stage stochastic programming and the convergence of its sample average approximation are established. Examples of this model are given, including the optimality conditions for stochastic programs, a Walras equilibrium problem and Wardrop flow equilibrium. We also formulate stochastic traffic assignments on arcs flow as a two-stage stochastic variational inequality based on Wardrop flow equilibrium and present numerical results of the Douglas–Rachford splitting method for the corresponding two-stage stochastic programming with recourse.     

Solving the logit-based stochastic user equilibrium problem with elastic demand based on the extended traffic network model

This paper proposes a novel extended traffic network model to solve the logit-based stochastic user equilibrium (SUE) problem with elastic demand. In this model, an extended traffic network is established by properly adding dummy nodes and links to the original traffic network. Based on the extended traffic network, the logit-based SUE problem with elastic demand is transformed to the SUE problem with fixed demand. Such problem is then further converted to a linearly constrained convex programming and addressed by a predictor–corrector interior point algorithm with polynomial complexity. A numerical example is provided to compare the proposed model with the method of successive averages (MSA). The numerical results indicate that the proposed model is more efficient and has a better convergence than the MSA.     

Stochastic integral equations applied to telecommunications traffic without delay

Modern telecommunication techniques case the problem of traffic handling in the framework of fairly general networks, as applied to traffic without delay but with virtually arbitrary service-time distributions. In this paper we use stochastic integral equations to deal with the case involving the most general input process and lost calls. For this purpose, Fortet's equation, unsolved so far in the general case, is solved to analyze the single trunk group model. The stationary case is then treated as a special case. Finally we study networks which satisfy a certain assumption of symmetry. The same general stochastic assumptions are maintained throughout the paper.     

Four species CA model for facing pedestrian traffic at rush hour

A model for the facing pedestrian traffic on a passage with a partition line at rush hour is developed. The model is described by a bi-directional cellular automaton (CA) model with four species. The CA model is not stochastic but deterministic. If the passage is congested and the local density is superior to the threshold, walkers to the east and to the west try to move separately changing their lane as the traffic rule is imposed on pedestrians at a high density. Walkers move freely ignoring the partition line at a low density. The traffic-rule effect at rush hour is taken into account in addition to the excluded-volume effect and bi-directionality. The pedestrian behavior under the traffic rule is clarified.     

Models for single-sector stochastic air traffic flow management under reduced airspace capacity

Air traffic efficiency is heavily influenced by unanticipated factors that result in capacity reduction. Of these factors, weather is the most significant cause of delays in airport and airspace operations. Considering weather-related uncertainty, air traffic flow management involves controlling air traffic through allocation of available airspace capacity to flights. The corresponding decision process results in a stochastic dynamic problem where aircraft on the ground and in the air are controlled based on the evolution of weather uncertainty. We focus on the single-sector version of the problem that is applicable to a majority of cases where a volume of airspace has reduced capacity due to convective weather. We model the decision process through stochastic integer programming formulations and computationally analyse it for tractability. We then demonstrate through actual flight schedule data that a simplistic but practically implementable approximation procedure is a generally effective solution approach for these models.