城市中观交通仿真的交通流车簇模型

为了解决城市交通仿真模型仿真速度和仿真精确度的平衡问题,针对城市交通流运行特征,同时考虑影响交通流运行的若干因素,如车辆数目、红绿灯控制等,提出一种中观交通仿真车辆群体模法.该模型结合了宏观模型和微观模型的优点,同时对应的交通流配流算法解决了传统模型的不足,城市交通仿真实验结果表明了车辆群体模型和分配算法的合理性和有效性.     

基于交通管理GIS的道路模型研究与实现

道路模型是城市地理信息系统的基础,在系统设计中既要考虑数据的组织和存储方式,又要顾及到其视觉效果.以交警地理信息系统为背景,以对路网要素标识的惟一性和道路模型的视觉效果为切入点,提出了一个多层复合道路模型.该模型通过运用基于地理位置的编码规则对路网要素的编码确保了对路网要素的惟一标识,通过引入参数化的道沿过渡线和绘制路面标线的方法提高了道路模型的视觉效果.实践证明,该道路模型能够较好地满足交通管理系统的应用需求.     

基于关联规则理论的道路交通事故数据挖掘模型

根据数据挖掘技术中的关联规则理论,提出"道路交通事故属性"的定义,并建立一种新的道路交通事故数据挖掘模型,利用改进的多维多数据类型的Apriori算法,从记录交通事故的数据库中发现潜在的、有价值、有联系的规律,用以指导交通管理部门找出道路黑点,并做出决策,杜绝事故隐患、减少事故发生,保障人们的生命和财产的安全。     

基于Kuhn-Munkres最优匹配的D2D资源分配算法设计

由于资源复用,D2D链路与蜂窝链路之间会产生同频干扰.为了抑制这种干扰,提出了一种基于Ku-hn-Munkres最优匹配的资源分配算法.该算法采用了图论中的Kuhn-Munkres最优匹配算法来实现最大限度的复用系统内的RB,达到提高系统吞吐量的目的.同时,通过使一对D2D用户复用多个RB进行通信以保证不同的QoS需求.最后,通过计算机仿真可以看出,该算法既可以有效地满足D2D用户的不同QoS需求,又提高了系统吞吐量.     

基于云模型的短时交通流预测方法研究

为了提高短时交通流预测的精确性,提出了一种基于云模型的短时交通流智能预测方法.该方法利用云模型拟合交通流,分别用历史交通流和当前交通流建立历史云和当前云,共同生成预测云,用采预测交通流.结合广州市某交叉口交通流量采集数据,进行了仿真试验,以平均绝对误差(MAE)和平均绝对百分比误差(MAPE)两个指标来衡量预测效果,结果表明了该预测方法具有较高的预测精度.该方法既考虑到交通流历史变化,又顾及交通流实时变化,同时将交通流做整体性处理,很好地避开了噪声引起的预测误差问题,兼顾了预测精度和实时性的要求.     

基于停车诱导信息板的最优停车场推荐的双层目标模型

现有停车诱导信息板的优化显示模型仅从驾车者的时间费用上进行优化,且多数仅支持输出各停车场空满状态.基于此,提出一种新的优化显示双层目标模型,增加诱导区域内各停车场空满程度最相近为第二层优化目标,并将给定目的地的推荐最优停车场作为模型的输出.该模型可在保证待停车辆寻找停车场造成的交通压力最小的前提下,诱导驾驶者的停车行为更加高效.通过算例分析表明:提出的双层目标模型,可以使停车诱导系统将待停车辆向更有利于驾驶者及停车场双方利益的方向诱导,克服了已有单目标模型和以排队长度为目标之一的双层目标模型最优解的不唯一性,同时达到了使总行驶时间最短和各停车场空满程度最相近的诱导目标.     

A model predictive control approach to the periodic implementation of the solutions of the optimal dynamic resource allocation problem

This paper proposes a model predictive control (MPC) approach to the periodic implementation of the optimal solutions of a class of resource allocation problems in which the allocation requirements and conditions repeat periodically over time. This special class of resource allocation problems includes many practical energy optimization problems such as load scheduling and generation dispatch. The convergence and robustness of the MPC algorithm is proved by invoking results from convex optimization. To illustrate the practical applications of the MPC algorithm, the energy optimization of a water pumping system is studied.     

公路交通收费系统多维模型的实现

针对公路信息化管理的需要,结合公路交通收费系统的特点,本文提出了一个新的多维模型数据仓库的解决方案,实现了多维数据仓库的设计.并探讨了用分类器器构建车辆欠费人群分类的模型。     

The effect of the asymmetry of road transportation networks on the traveling salesman problem

The routing of vehicles on road transportation networks is an area of great importance to transportation planners within scientific literature. This field includes well known and studied problems like traveling salesman problems or TSP or the more realistic asymmetric variant or ATSP, whose applications extend to other areas of transport and operations research. This work studies the effect that the asymmetry of road transportation networks, geographical location and territory have over TSP and ATSP methods. We conduct comprehensive experiments in order to assess the effects that these factors have on some of the best known algorithms for the TSP/ATSP. We demonstrate that all these factors have a significant influence in solution time and quality. Furthermore, we show that the solutions obtained with Euclidean matrices and those obtained with real distance matrices differ significantly.     

基于递归神经网络的网络流量组合预测模型

为了提高网络流量的预测精度,提出了一种基于Elman递归神经网络,小波和自回归的网络流量组合预测模型.对流量时间序列进行小波分解,得到小波变换尺度系数序列和小波系数序列,对具有平稳特征的尺度系数序列用AR模型进行预测:而对体现了网络流量非线性、非平稳特性的小波系数序列使用Elman递归神经网络进行预测,最后通过Mallat算法重构得到网络流量的预测值.     

基于小波变换和ARMA-LSSVM的忙时话务量预测

为提高受多种因素影响的话务量数据的预测精度和稳定性,提出一种考虑多因素影响的基于小波变换和自回归滑动平均(ARMA)-最小二乘支持向量机(LSSVM)的话务量组合预测模型。对忙时话务量数据进行相关性分析,得出影响话务量的重要因子;利用小波变换对数据进行分解和重构,得到低频分量和高频分量;将低频分量输入ARMA模型进行预测,将高频分量和话务量重要影响因子输入粒子群算法优化的LSSVM模型进行预测,将两组预测结果合成。实验结果表明,该模型进一步提高了预测精度和稳定性。     

基于XML和J2EE的远程教育资源共享模型研究及实现

随着远程教育的不断发展，如何进行教育资源建设，实现教育资源的共享，已成为远程教育中迫切需要解决的重要课题。对远程教育和计算机中新兴的XML和J2EE技术进行了研究，从面向对象的角度出发构建了一个基于XML和J2EE的远程教育资源共享模型，并对该模型的设计及实现过程进行了分析。     

基于设备可靠性分析的最优投资策略

定义了设备可靠性的概念,给出了设备可靠性的评价模型,对化工设备在固定时间内运行的可靠性进行了分析,提出了设备投资的最优化策略的数学模型和求解策略。结合实例给出了如何在满足系统可靠性要求的前提下实现设备最优投资的策略,并计算出了所需备用设备的最小数量。结果表明此策略可以广泛应用于工程实践中。     

Modelling and asset allocation for financial markets based on a stochastic volatility microstructure model

On the basis of the market microstructure theory, a continuous time microstructure model is proposed for describing the dynamics of financial markets with stochastic volatility property. From the microstructure model, one may obtain the estimates of two state variables, which represent the market excess demand and liquidity respectively but cannot be directly observed. Based on the indirectly obtained excess demand information instead of the prediction of price, a simple asset dynamic allocation approach is investigated. The local linearization method, nonlinear Kalman filter and maximum likelihood method-based estimation approach for the microstructure model proposed is presented. Case studies on the financial markets modelling and the estimated model-based asset dynamic allocation control for the JPY/USD (Japanese Yen/US Dollar) exchange rate and Japan TOPIX (Tokyo stock Price IndeX) show a satisfactory modelling precision and dynamic allocation performance.     

基于改进遗传算法的路网路径优化方法

根据动态交通信息模型,用遗传算法求解最优路径问题,并根据编码的特点提出了一种新的迭代算子。文章后部分通过计算机仿真证明了算法的可行性。软件实现采用VC++平台。     

Multi-driver agent-based traffic simulation systems for evaluating the effects of advanced driver assistance systems on road traffic accidents

A recent investigation revealed that there is a substantiated need for the development of a micro-simulation system designed for traffic safety assessment. This paper describes the development of a road traffic simulation system, which uses a ‘nanoscopic model’ of driver behaviour and an integrated analysis-evaluation system designed for traffic safety assessment. The primary focus is on estimating the effects of an advanced driver assistance system thereby reducing traffic accidents. The effectiveness and validity of the present system are demonstrated through comparison with measured traffic data. This paper also proposes algorithms embedded in a ‘driver-agent’, for recognising driver’s intentions regarding choosing steering-control modes, lateral control tasks, and the driving mood. This is because the driver assistance systems need to recognise the driver’s intention when choosing steering-control. The results of a simulation study, using the data drawn from actual driving, show that the systems would achieve a high recognition capability. As an example of how driving mood recognition applies to driver assistance systems, an advanced steering system and the adaptability to the driver’s mood, have also been presented.     

The approximate solution of the Euclidean traveling salesman problem on a CRAY X-MP

The efficient use of MIMD computers calls for a careful choice of adequate algorithms as for an implementation taking into account the particular architecture. To demonstrate these facts, a parallel algorithm to find an approximate solution to the Euclidean Traveling Salesman Problem (ETSP) is presented. The algorithm is a parallelization of Karp's partitioning algorithm. It is a divide-and-conquer method for solving the ETSP approximately. Since the successor vertex to any vertex in the tour is usually a nearby vertex, the problem can be ‘geographically’ partitioned into subproblems which then can be solved independently. The resulting subtours can be combined into a single tour which is an approximate solution to the ETSP. The algorithm is implemented on a CRAY X-MP with two and four processors, and results using macrotasking and microtasking are presented.     

基于多类别支持向量机的城市交通网络模式分类研究

在网络层次上进行区域交通信号控制、交通分配和路径诱导是缓解交通堵塞的有效途径之一。为进一步提高城市交通网络分类检测的准确性,将支持向量机（Support Vector Machine）应用于交通事件的模式分类研究。通过提出一种基于多类别支持向量机的交通模式分类方法,设计了适合该检测系统的网络结构。仿真结果表明：相对于其他算法,城市交通网络的状态可分为数量有限且不同类型的模式,并且这些模式不断重复出现,当系统识别出网络处于某种模式时,就可参照事先确定的优化参数及策略进行交通控制和诱导,以缓解交通拥塞,提高交通系统的运行效率。该网络结构对于小样本数据具有检测率高、误报率低的优点,完全适用于城市交通的模式分类,同时也存在不足之处,指出了今后进一步研究的方向。     

基于GPRS的远程监控系统集中器的设计

提出了一种基于通用无线分组数据业务GPRS的远程监控系统集中器的设计方案，阐述了由单片机MSP430F133及GR47通信模块构成的集中器的硬件结构和软件实现。通过比较集中器通讯实现方式的差异，表明采用GPRS和RS-485组合通讯的集中器设计在远程监控系统中具有一定的优势。     

基于自回归模型的溶液浓度测定方法研究

当物理和化学因素的影响导致溶液不满足朗伯-比尔定律时,A-c曲线将偏离直线而弯曲,这给直接利用吸光光度法测定溶液的浓度带来了极大的不便。本文提出采用自回归(Auto-Regressive,AR)模型的溶液浓度测定方法。该方法采用AR模型对不同浓度溶液的紫外透光率曲线进行建模,根据模型求解的特征传递函数确定溶液的特征距离,并建立特征距离—浓度对照表,然后测定未知溶液的紫外透光率曲线,确定其特征距离,并利用特征距离—浓度对照表进行插值以估计溶液浓度。由于该方法是从溶液光谱的本质出发进行分析,所以该方法不受朗伯-比尔定律的限制,不仅可以准确估计低浓度溶液的浓度,还可突破朗伯-比尔定律的限制准确估计高浓度溶液的浓度。采用该方法对KMnO_4溶液浓度进行测定,实验结果表明,该方法对溶液浓度的估计相对误差小于0.8%。