机车车体结构模态的有限元分析

建立了一种新型交流传动内燃机车车体详细的有限元模型,描述了该车体的振动模态,并分析了影响该车体结构的主要影响因素,为机车车体结构轻量化设计提供了参考依据。     

船舶电力系统浮动频压节能技术的研究与应用

船舶节能技术是目前研究的最重要船舶技术之一。基于船舶电力系统降频降压节能技术可行性研究,设计出船舶电力系统浮动频压节能控制器,实现了全船用电设备的总体节能。经实船节能效果试验,平均节电9.85%、节油9.53%。鉴于此,建议修改完善钢质海船入级与建造规范,以利于此项新节能技术的推广应用。     

基于Backstepping的船舶航向跟踪控制

针对线性船舶运动模型航向改变过程中，往往引起快速大的舵动，产生严重的水动力非线性的问题，设计基于backstepping的非线性船舶航向跟踪控制器。它是将Lyapunov函数的选取与控制器的设计相结合的一种回归设计方法，通过从系统的最低阶次微分方程开始，引入虚拟控制的概念，一步一步设计满足要求的虚拟控制，最终设计出真正的控制律，保证了闭环系统是全局渐近稳定的。在计算机仿真研究中，以大连海事大学“育龙”号实习船为设计实例，验证所提出的控制器的有效性。     

电喷发动机传感器的工作原理与检修

系统地阐述了电喷发动机常用传感器的结构、种类及工作原理,给出了它们的输出特性并进行了归纳,同时也列举了各传感器的检修方法。     

西部地区公路货运周转量可拓聚类预测

文章以可拓聚类的原理和一般预测过程为依据,结合我国西部地区公路货运周转量预测的特点,在分析国外先进经验的基础上,完成对西部地区公路货运周转量的预测。基于GDP和进出口总额的公路货运周转量可拓聚类预测,以区间的形式表示。可以相对减少对单纯点的数值预测的局限性和误差,当给定一个未来环境因素时,可以判定出公路货运周转量变化的类型,从而预测未来公路货运周转量的变化范围,得到预测结果是可行的。     

西康线长哨车站特殊水文与多线斜交桥设计

长哨、八亩坪乾佑河大桥是西康线上控制线路方案的重点桥渡 ,也是目前国内一座斜交角度较大的多线桥 .笔者介绍了桥址处的特殊水文、水工模型试验及设计经过 ,对今后多线桥的设计提供帮助     

基于Web的铁路施工方案管理信息系统研究

介绍了基于计算机网络的铁路施工方案管理信息系统,系统目标,系统特点,系统功能和网络结构,论述了基于Web的PowerBuilder8可视化开发工具下系统实现的关键技术.     

厂内机动车辆驾驶自学与培训系统设计与应用

厂内机动车辆驾驶自学与培训系统改变职工教育的形式和方法,解决职工的工学矛盾,为厂内机动车辆驾驶人员的理论知识和实际操作技能的提高提供一个新的学习平台和培训方式.     

Real time location prediction with taxi-GPS data streams

The prediction of the destination location at the time of pickup is an important problem with potential for substantial impact on the efficiency of a GPS-enabled taxi service. While this problem has been explored earlier in the batch data set-up, we propose in this paper new solutions in the streaming data set-up. We examine four incremental learning methods using a damped window model namely, Multivariate multiple regression, Spherical-spherical regression, Randomized spherical K-NN regression and an Ensemble of these methods for their effectiveness in solving the destination prediction problem. The performance of these methods on several large datasets are evaluated using suitably chosen metrics and they were also compared with some other existing methods. We found that the Multivariate multiple regression method has the best performance in terms of prediction accuracy but the Spherical-spherical regression method is the best performer when we take into account the accuracy time trade-off criterion. The next pickup location problem, where we are interested in predicting the next pickup location for a taxi given the dropoff location coordinates of the previous trip as input is also considered and the aforementioned methods are examined for their suitability using real world datasets. As in the case of destination prediction problem, here also we find that the Multivariate multiple regression method gives better performance than the rest when we consider prediction accuracy but the Spherical-spherical regression method is the best performer when the accuracy-time trade-off criterion is taken into account.     

Factors affecting temporal changes in mode choice model parameters

In travel demand forecasting models, parameters are often assumed to be stable over time. The stability of these parameters, however, has been questioned. This study investigates the factors affecting temporal changes in mode choice model parameters using a method proposed by the author that jointly utilises repeated cross-sectional data. In this method, the parameters are assumed to follow functional forms and the parameter changes are modelled endogenously. While the author’s previous studies assumed that all parameters are the same function of the same variable, this study assumes that different parameters are different functions of different variables, including time (year) and macro-economic variables. The paper describes a case study of a journey-to-work mode choice analysis for Nagoya, Japan, that examines 288 combinations of the functional forms and variables. The analysis found that the functions of time had serious over-fitting problems and that parameter changes are more closely related to economic factors.