公路建设中水土流失预测与防治的研究

分析了高等级公路建设中水土流失的成因,利用水土流失预测数学模型对可能造成的水土流失量进行了估算,根据工程水土流失的特点、危害程度和防治目标,介绍了分区、分期的防治措施。可为高等级公路建设中的水土保持、生态环境建设及其周边地区环境资源的开发利用提供借鉴和参考。     

Stochastic prediction of train delays in real-time using Bayesian networks

In this paper we present a stochastic model for predicting the propagation of train delays based on Bayesian networks. This method can efficiently represent and compute the complex stochastic inference between random variables. Moreover, it allows updating the probability distributions and reducing the uncertainty of future train delays in real time under the assumption that more information continuously becomes available from the monitoring system. The dynamics of a train delay over time and space is presented as a stochastic process that describes the evolution of the time-dependent random variable. This approach is further extended by modelling the interdependence between trains that share the same infrastructure or have a scheduled passenger transfer. The model is applied on a set of historical traffic realisation data from the part of a busy corridor in Sweden. We present the results and analyse the accuracy of predictions as well as the evolution of probability distributions of event delays over time. The presented method is important for making better predictions for train traffic, that are not only based on static, offline collected data, but are able to positively include the dynamic characteristics of the continuously changing delays.     

利用绿化降低船舶噪音的探索

针对船舶噪音与居住环境的矛盾逐渐突出，提出了利用绿化手段，降低船舶噪音对环境的污染，扩展了绿化的效能。     

大客车车身典型零构件疲劳寿命预测

本文以大客车车身典型零件为研究对象，采用局部应力反应变法预测承受高周载荷零构件的疲劳寿命。     

基于单参数的Lagrangian支持向量回归算法及其应用

支持向量机(Support Vector Machines,SVM)是基于统计学习理论框架下的一种处理非线性分类和非线性回归的有效方法。由于具有完备的理论基础和出色的学习性能,该方法已成为当前国际机器学习界的研究热点,能较好地解决小样本、高维数、非线性和局部极小点等实际问题。这里提出了一种基于单参数的拉格朗日(Lagrangian)支持向量回归算法,并将该算法应用在外贸货物吞吐量预测中。估算结果证明了这种改进的支持向量回归算法在吞吐量预测中的有效性和实用性。