换热器熵产分析

在余热发电系统中,换热器直接将热源中的热量吸收传递到系统中,然后将从透平中出来的工质冷凝,其性能好坏直接影响了整个系统的效率。本文引入了无量纲熵产数Ns表示换热器的热力完善程度,并且通过熵产分析,揭示了换热器能耗产生的原因,确定了最佳的热力参数匹配,能够更好的完成节能目的。对于工业中余热发电项目的优化具有重要参考意义。     

导弹仿真模型验证技术与平台设计

根据靶场导弹试验需求和建模与仿真VV＆A标准规范,设计了基于仿真全生命周期的导弹仿真模型验证过程和内容,重点分析了基于时域和频域分析方法的导弹模型验证技术。依据仿真模型验证应用,设计并开发了导弹模型验证自动化平台,文章详细描述了自动化平台的总体结构和功能,并以具体验证实例分析了模型验证技术应用的可行性。     

信号协调控制下城市干道运行效率评价研究

以信号协调控制的城市干道为研究对象,从平均行程延误、排队长度、停车率、行程车速及饱和度方面建立干道运行效率评价指标,将信息论中熵值理论引入干道运行效率评价中,确定各评价指标的权重。基于未确知测度理论,建立城市干道运行效率等级评价和排序模型。以某具体干道作为实例分析,结果表明：基于熵权的未确知测度综合评价用于干道信号协调控制运行效率评价是切实可行的。     

基于驾驶行为和信息熵的道路交通安全风险预估

为了精准有效地进行交通事故预防预警，基于车辆OBD驾驶行为数据及信息熵理论，提出了城市道路交通安全风险预估方法。首先，分析异常驾驶行为高发位置与道路交通事故发生位置的关联性；其次，构建以道路交通安全熵为一级指标，急加速率、急减速率、急转弯率、超速率、高速空挡滑行率为二级指标的道路交通安全风险预估指标体系，提出了基于改进熵权法的道路交通安全熵计算方法；然后，基于密度聚类、K-means聚类提出了道路交通安全风险等级数确定方法，并基于K-means聚类建立了风险等级阈值计算方法。研究结果表明：异常驾驶行为高发位置与交通事故发生位置具有一致性；通过对log对数底数选择优化、二级指标零值处理、指标权重分段计算3个步骤改进的熵权法，可弥补log对数函数无法计算零值指标熵值的缺陷，避免指标权重为负、指标熵值与权重反映信息不一致的现象；两步聚类避免了孤立数据点对安全风险等级划分的影响。以重庆市4条城市道路（总长约38 km）进行实例验证后得出，道路交通安全熵与交通事故表征的道路交通安全状态趋势一致；道路交通安全风险等级可划分为高、低风险2级，道路交通安全熵优化阈值为0.042，最后，风险等级划分准确率为87.88%。研究成果可为道路交通安全风险点辨识、交通事故预防预警提供有效的技术支持。     

Bicriterion shortest path problem with a general nonadditive cost

A bicriterion shortest path problem with a general nonadditive cost seeks to optimize a combination of two path costs, one of which is evaluated by a nonlinear function. This paper first identifies a number of emerging transportation applications for which such a shortest path problem might be considered a core subproblem. We propose to first approximate the general nonlinear cost function with a piecewise linear counterpart, and then solve each linear subproblem sequentially. A specialized algorithm is developed to solve the subproblems, which makes use of the efficient path set (or the convex hull) to update upper and lower bounds of the original problem. Conditions under which the solution to a subproblem must belong to the efficient path set are specified. Accordingly, we show that the optimal path must be efficient if the nonlinear cost function is concave. If the optimal path to a subproblem is not efficient, partial path enumeration, implemented using a simple K-shortest path ranking procedure, is conducted to close the gap. The proposed algorithm includes strategies aiming to expedite path enumeration by using upper bounds derived from the efficient path set. Numerical experiments are conducted to demonstrate correctness and effectiveness of the proposed algorithm.     

Route Selection for Railway Passengers: A Multi-objective Model and Optimization Algorithm

With an increased operating speed in Chinese railways in recent years, the number of passengers traveling by trains has been significantly increasing. The research issue is regarding how passengers select their routes when there are no direct trains. Previous studies have dealt with the route selection problem as a multi-objective optimization. The study began by setting up a transportation network which encompasses the departure and terminal stations along with important intermediate stations. Then, six key factors are analyzed and formulated using a multi-objective model, consisting of the train-running time, railway fare, transfer frequencies, distances between transfer stations, transfer interval time, and travel comfort. Furthermore, a two-phase algorithm is employed to solve the model. A rapid searching algorithm for feasible routes based on the train timetable is established, then the weight vector is assigned by introducing the information entropy to obtain satisfied routes. In the end, the two-phase algorithm is tested respectively for railway passengers from Lanzhou to Beijing (with direct trains) and from Lanzhou to Changchun (without direct trains), and the results show that the proposed model and solution algorithm are efficient for obtaining satisfactory routes.     

Automated driving recognition technologies for adverse weather conditions

During automated driving in urban areas, decisions must be made while recognizing the surrounding environment using sensors such as camera, Light Detection and Ranging (LiDAR), millimeter-wave radar (MWR), and the global navigation satellite system (GNSS). The ability to drive under various environmental conditions is an important issue for automated driving on any road. In order to introduce the automated vehicles into the markets, the ability to evaluate various traffic conditions and navigate safely presents serious challenges. Another important challenge is the development of a robust recognition system can account for adverse weather conditions. Sun glare, rain, fog, and snow are adverse weather conditions that can occur in the driving environment. This paper summarizes research focused on automated driving technologies and discuss challenges to identifying adverse weather and other situations that make driving difficult, thus complicating the introduction of automated vehicles to the market.     

公路软基处理方案优选的熵权模糊物元决策法

针对目前公路软基处理方案优选决策中存在的不足,将模糊物元分析应用到公路软基处理方案优选决策中,建立基于熵权的模糊物元决策方法.该方法把各种软基处理方案作为物元的事物,用方案的各项评价指标及其相应的模糊量值构造复合模糊物元.采用熵权与决策者的主观权重相结合的方法确定评价指标的综合权重,使之既能反映决策者的主观偏好,又能反映指标的客观分布特征,使权重确定更加合理.通过计算各比较物元与标准模糊物元之间的海明贴近度来实现方案的排序与择优.最后,以苏嘉杭高速公路软基处理方案优选为例,结果说明该方法是有效、可行的.     

耗散结构及熵变理论在区域交通系统中的应用探讨

区域交通系统是一耗散结构。基于交通系统的特性,选择区域交通网络有效路段上的平均交通拥挤度为序参量,来描述区域交通系统的演化过程和方向。通过分析区域交通系统的耗散结构属性,利用熵理论和信息论,建立了区域交通系统熵测算模型,并利用该模型对1998￣2004年间北京都市圈交通系统熵进行了实证性测算研究,并根据熵变理论,对该区域内交通系统演化过程及方向作出分析。     

交通管制条件下城市道路网络模型及分配算法研究

城市道路网络模型及其算法是城市道路网络分析和分配的基础。本文首先分析了交通管制条件下原有城市道路网络模型和算法的不足,在此基础上提出一种改进模型和算法,并给出算例。这种改进的模型和算法能较好地满足实际分配的要求,在交通规划、交通管理和交通流模拟中都有着十分广阔的应用前景,且已经被成功地应用于郑州市综合交通规划中。