高职高专电子商务专业双语教学刍议

本文首先从社会需求、专业改革、人才培养等角度论述了高职高专电子商务专业双语教学的必要性,并从语言学的角度论述了其理论基础。然后分析了适合我国高职高专电子商务专业双语教学的教学模式,最后分析了存在的问题及对策。     

城乡一体化的公交服务体系规划理论与实践研究

随着我国经济的不断发展,公共交通发挥着越来越重要的作用。城市化进程的加快和道路基础设施的改善为城乡一体化的公共交通体系提供了广阔的发展前景。研究了城乡一体化的公共交通服务体系规划的理论框架,并以汕头市为应用实例,提出了规划的可行性和实践性。     

自动变速器控制技术研究

自动变速器的控制技术影响到变速器使用性能,介绍现代控制理论在自动变速器控制中的应用,如换档点控制,变矩器闭锁离合器控制,换档质量控制,适应性控制,模糊控制,容错控制等理论。     

农村公路网规划建设的思考

对现有道路投资理论、道路投资主体的变化以及政府职能等影响农村道路网建设的因素进行分析,得出造成农村路网落后的原因。从政治,经济、公平等方面入手,分析农村路网规划建设的必要性以及内在规律性。     

两万吨组合列车制动特性

为了减小重载列车纵向冲动,提高列车制动特性的同步性,利用基于空气流动理论的空气制动仿真系统,计算了列车制动系统的制动管路和各缸室的瞬态气体状态,获得制动系统动态特性,预测了两万吨组合列车的紧急制动与常用制动特性,分析了制动波的传递特性。计算结果表明:两组合列车可以缩小最大制动时间差50%,如果在两组合列车尾部配置机车,最大制动时间差可以缩小75%,四组合列车最大制动时间差可以缩小75%;紧急制动波速等速前后传递,常用制动时向前传递的制动波波速要比向后传递的制动波波速小。可见,组合列车是一种改善列车制动同步性的理想方式。     

广义梯度理论中交通文化梯度的解释结构模型研究

为了对交通文化进行深入研究,作者简要介绍了广义梯度理论的主要思想及其对梯度理论的发展,并以交通文化梯度的含义和内在关系为研究对象,在广义梯度理论的指导下,找出了26个交通文化梯度因素,确定了系统各要素之间的相互关系和层级递阶结构.采用系统工程的方法,利用结构方程对交通梯度进行系统和全面的分析与研究,最终得到一个基于广义梯度理论的交通文化梯度解释结构模型.得到的模型不仅可以清楚刻画交通文化梯度各要素之间的层级关系,而且为设计交通文化梯度评价指标打下了基础.     

基于键图理论对安装EPS系统的车辆操纵稳定性的仿真分析

应用键图理论建立电动助力转向系统(EPS)的模型,将电动助力转向系统的键图模型和matlab的simulink仿真方框图相连接,并利用simulink的可视化功能实现汽车操纵稳定性的可视化仿真,仿真结果表明,将simulink仿真工具箱与键图模型相结合,可使汽车性能分析研究更为直观和简洁.     

Verifying liner Shipping Alliance’s stability by applying core theory

The core is a vital concept in cooperative game theory and has been widely used in analyzing alliance’s stability. It is especially interesting to apply core theory in liner shipping market due to the latter’s exceptional characteristic of non-homogeneous cost curves as well as divisible and fluctuant demand. Having observed some new phenomena and trends in the industry, this paper studies the economic performance and stability of liner shipping alliance by applying core theory where business cooperation is partly realized by delivering joint-service with mega container ships. To demonstrate the core situation in liner shipping alliance, a cost function is first identified on the basis of two assumptions regarding cooperation: 1) sharing or pooling vessels and 2) deploying mega container ships if needed. Taking cost functions as basis, two conditions of approaching core may be groomed, i.e., collective rationality and individual rationality. The first condition is discussed from the perspective of market, while the second condition is studied within the alliance. Stability of liner shipping alliance is then observed based on these two conditions. An illustrative case study is conducted in order to show some implications and explicitly clarify the theory.     

高职《建筑材料》课程教学改革与实践

针对建筑材料课程在理论和实践课教学中存在的不足,就建筑材料理论教学和实践教学及教学方法的改革提出几点可行性建议,从而激发学生的学习兴趣,培养其创新能力,为毕业生在今后的设计和施工工作中合理选材打下坚实的基础。     

Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China

Short-term forecasting of high-speed rail (HSR) passenger flow provides daily ridership estimates that account for day-to-day demand variations in the near future (e.g., next week, next month). It is one of the most critical tasks in high-speed passenger rail planning, operational decision-making and dynamic operation adjustment. An accurate short-term HSR demand prediction provides a basis for effective rail revenue management. In this paper, a hybrid short-term demand forecasting approach is developed by combining the ensemble empirical mode decomposition (EEMD) and grey support vector machine (GSVM) models. There are three steps in this hybrid forecasting approach: (i) decompose short-term passenger flow data with noises into a number of intrinsic mode functions (IMFs) and a trend term; (ii) predict each IMF using GSVM calibrated by the particle swarm optimization (PSO); (iii) reconstruct the refined IMF components to produce the final predicted daily HSR passenger flow, where the PSO is also applied to achieve the optimal refactoring combination. This innovative hybrid approach is demonstrated with three typical origin–destination pairs along the Wuhan-Guangzhou HSR in China. Mean absolute percentage errors of the EEMD-GSVM predictions using testing sets are 6.7%, 5.1% and 6.5%, respectively, which are much lower than those of two existing forecasting approaches (support vector machine and autoregressive integrated moving average). Application results indicate that the proposed hybrid forecasting approach performs well in terms of prediction accuracy and is especially suitable for short-term HSR passenger flow forecasting.