基于模糊线性回归分析的编组站运营指标预测方法

运用模糊线性回归分析方法,建立编组站运营指标的模糊预测模型。利用该模型,对向塘西编组站中时进行了预测。在对中时影响因素分析的基础上,选取办理车数、有调中转车数、无调中转车数、折角车流量、货物列车到发列数和到发均衡程度等6个影响因素,结合车站近几年相关历史数据,确定了中时与6个影响因素之间的模糊函数关系。依据此函数关系对未来时期的中时进行了预测,预测结果表明所提出的运营指标预测方法有较好的适用性。     

四边固定支承矩形薄板振动分析的有限积分变换法

利用双重有限余弦积分变换的方法推导出了四边固定支承条件下,矩形薄板的固有频率和振型的解析解表达式.由于在求解过程中不需要事先人为地选取挠度函数,而是从弹性薄板的基本振动方程出发,直接利用数学的方法求出可以完全满足四边固定支承的边界条件,弹性矩形薄板的固有频率和振型解析解,使得问题的求解更加合理化.最后,还给出了计算实例来验证文中所采用的方法以及所推导出的公式的正确性.     

A methodological approach for developing and assessing business models for flexible transport systems

Flexible transport services include a wide range of demand responsive transport systems that provide non-conventional passenger and freight transportation services. Several alternative business models varying according to the local market conditions, the socio-economic, legal, and institutional framework may be developed for the provision of Flexible Transport Systems (FTS). The objective of this paper is twofold: first to present an integrated methodological framework for developing and assessing alternative FTS business models and second to demonstrate its applicability to a case study regarding the prioritization of alternative FTS business models for the provision of flexible passenger transport services in Helsinki.

新疆公路运输量发展预测

在分析新疆经济、交通运输发展的基础上,采用回归分析法、三次指数平滑法、灰色预测方法和弹性系数法等多种方法预测新疆2010年、2015年、2020年的公路运输需求,并结合这些方法,采用了基于误差权重因子的多种方法组合预测的新方法,对新疆公路运输需求量进行了优化组合预测。对新疆未来3个特征年预测结果的分析表明,该预测方法是合理而有效的。     

Distributed support modelling for vertical track dynamic analysis

The finite length nature of rail-pad supports is characterised by a Timoshenko beam element formulation over an elastic foundation, giving rise to the distributed support element. The new element is integrated into a vertical track model, which is solved in frequency and time domain. The developed formulation is obtained by solving the governing equations of a Timoshenko beam for this particular case. The interaction between sleeper and rail via the elastic connection is considered in an analytical, compact and efficient way. The modelling technique results in realistic amplitudes of the ‘pinned–pinned’ vibration mode and, additionally, it leads to a smooth evolution of the contact force temporal response and to reduced amplitudes of the rail vertical oscillation, as compared to the results from concentrated support models. Simulations are performed for both parametric and sinusoidal roughness excitation. The model of support proposed here is compared with a previous finite length model developed by other authors, coming to the conclusion that the proposed model gives accurate results at a reduced computational cost.     

BP神经网络在解决电力消耗问题中的应用

由于BP神经网络在解决非线性复杂系统中存在很大的优势,以江西省1991—2011年人口、经济和耗电量等数据为研究对象,利用BP神经网络构建耗电量预测模型。模型一利用1991—2009年人口、经济和耗电量等数据作为训练样本,以2010—2011年作为测试样本来验证网络的准确性,再根据历史人口、经济等数据来预测历史耗电量;模型二采用传统的多元回归分析法,对非线性多元函数进行多元线性回归,通过回归模型得到的参数来预测耗电量。结果表明,模型一收敛性较好,所得预测结果绝对误差较小,而模型二传统方法得到的预测结果误差较大,因此,利用BP神经网络预测的结果具有非常大的参考价值,证明BP神经网络应用在电力消耗中的应用是可行的。     

Factors influencing support for local transportation sales tax measures

Sales tax measures passed at the local level and dedicated to transportation projects have become increasingly popular in the United States. While revenues from fuel taxes stagnate, growth of local transportation sales taxes (LTSTs), most approved in local elections, has led to a gradual shift of the financial base for transportation projects away from user fees and toward broader-based taxes. In this study, the relationship between voter support and the social, political, and geographic characteristics of the voters is explored. Using precinct-level voting data and census demographic data for three local transportation sales tax elections in Sonoma County, in the San Francisco Metropolitan area of California, regression models were constructed to analyze this relationship. In addition, the relationship between the outcomes of the three measures was explored to better understand which transportation projects might have garnered more support for the successful measure. It was found that the closer voters lived to the transportation projects to be funded, the greater their support. Higher incomes were also positively related to support, controlling for other variables. Political leanings were found to affect support, with the direction of the effect dependent upon the project list in each measure’s expenditure plan. Finally, it appears that the latest measure, which passed successfully, benefited greatly from its multi-modal expenditure plan.     

组合预测模型在上海内河港口吞吐量预测中的应用

建立时间序列和二元线性回归的组合预测模型,对上海内河港口2010年、2015年和2020年的货物吞吐量水平进行了预测。研究发现,组合预测模型相比单个预测方法具有较高的精度,能够较准确地预测上海内河港口货物吞吐量。     

青岛港港口吞吐量与青岛市GDP关系的计量经济分析

运用线性回归、辅助函数等计量经济学方法,通过使用Eviews软件对青岛港港口吞吐量与该市GDP之间的定量关系进行了回归分析,并进一步分析了港口吞吐量与GDP之间的关系。