Comparison of advanced imputation algorithms for detection of transportation mode and activity episode using GPS data

Global Positioning System (GPS) technologies have been increasingly considered as an alternative to traditional travel survey methods to collect activity-travel data. Algorithms applied to extract activity-travel patterns vary from informal ad-hoc decision rules to advanced machine learning methods and have different accuracy. This paper systematically compares the relative performance of different algorithms for the detection of transportation modes and activity episodes. In particular, naive Bayesian, Bayesian network, logistic regression, multilayer perceptron, support vector machine, decision table, and C4.5 algorithms are selected and compared for the same data according to their overall error rates and hit ratios. Results show that the Bayesian network has a better performance than the other algorithms in terms of the percentage correctly identified instances and Kappa values for both the training data and test data, in the sense that the Bayesian network is relatively efficient and generalizable in the context of GPS data imputation.     

Multiobjective optimisation of bogie suspension to boost speed on curves

To improve safety and maximum admissible speed on different operational scenarios, multiobjective optimisation of bogie suspension components of a one-car railway vehicle model is considered. The vehicle model has 50 degrees of freedom and is developed in multibody dynamics software SIMPACK. Track shift force, running stability, and risk of derailment are selected as safety objective functions. The improved maximum admissible speeds of the vehicle on curves are determined based on the track plane accelerations up to 1.5?m/s². To attenuate the number of design parameters for optimisation and improve the computational efficiency, a global sensitivity analysis is accomplished using the multiplicative dimensional reduction method (M-DRM). A multistep optimisation routine based on genetic algorithm (GA) and MATLAB/SIMPACK co-simulation is executed at three levels. The bogie conventional secondary and primary suspension components are chosen as the design parameters in the first two steps, respectively. In the last step semi-active suspension is in focus. The input electrical current to magnetorheological yaw dampers is optimised to guarantee an appropriate safety level. Semi-active controllers are also applied and the respective effects on bogie dynamics are explored. The safety Pareto optimised results are compared with those associated with in-service values. The global sensitivity analysis and multistep approach significantly reduced the number of design parameters and improved the computational efficiency of the optimisation. Furthermore, using the optimised values of design parameters give the possibility to run the vehicle up to 13% faster on curves while a satisfactory safety level is guaranteed. The results obtained can be used in Pareto optimisation and active bogie suspension design problems.     

浅析造船合同下的船舶设计问题

船舶作为一种特殊的商品,交易过程复杂,技术规范要求高,合同生效开始,船厂开始自己或委托设计公司根据船舶技术规格书设计船舶,送交船级社及有关政府当局和船东审查。建造合同是设计的依据,船厂在履行合同的过程中要明确设计的责任和权利,从源头上把设计风险降到最低。文章从管理和实际应用角度,阐述了造船合同下船舶设计中应该注意的要点,在此基础上提出提高船舶设计管理水平的建议及对策。     

基于交互式多目标遗传算法的混凝土桥面板维修优化

为了保证桥梁结构安全,并使维修效果最好,研究了如何确定桥面板最佳维修策略的问题。建立了桥面板维修的多目标优化模型。提出一种基于交互式遗传算法的维修策略优化方法,通过非精确偏好信息引导遗传搜索,使种群朝着多个目标的最佳综合性能进化。引入适应值共享方法增加种群的多样性,最终获得符合决策者偏好的解集。并通过算例进行了分析验证。结果表明,基于交互式多目标遗传算法的混凝土桥面板维修优化方法可以在有限的桥梁维修资源和良好的维修效果之间进行折衷,不仅获得一组比较理想的维修方法组合,还可以考虑决策者的个人倾向,降低了维修策略的选择难度,为桥梁管理者提供了有力的决策支持。     

混合小生境遗传-模拟退火算法在动态交通分配中的应用

为了解决已有的动态交通分配模型普遍存在的优化计算时间过长,严重影响网络规模扩展的问题,提出了一种新的动态交通分配优化算法。将模拟退火和隔离小生境技术有机地结合起来,融入到遗传训练过程中形成了一种混合小生境遗传-模拟退火算法,不仅可以有效地避免传统遗传算法可能出现的不收敛现象,加快进化速度,具有更强的全局寻优能力,而且计算速度和算法稳定性也得到提高。将其与Papageorgiou M.提出的动态交通分配模型框架相结合,设计了动态交通分配的快速模拟优化算法,并进行了实例研究。仿真结果表明,新的优化算法显著降低了优化计算时间,大大提高了动态交通分配模型的实用价值。     

土钉支护计算模型及其优化方法探讨

针对目前土钉支护优化设计方法中存在的一些缺陷和不足,深入研究了土钉支护的工作机理,尤其是土钉的受力情况,提出了以钉土间抗剪强度为土钉最大拉力分配刚度的原则,并给出了土钉最大拉力分配系数的计算公式;结合土钉支护整体稳定性的极限平衡分析,推导了土钉最大拉力的计算方法,将计算结果与现场测试进行对比分析证明了该方法的合理性;在深入分析土钉长度计算模型的基础上,建立了以单位支护面积的土钉长度为目标函数的土钉支护优化设计模型;通过引入改进的模拟退火算法和几何控制参数法,探讨了土钉支护优化设计方法的具体实施步骤,并开发出相应的计算程序。工程实例分析表明:所建立的优化设计方法在能保证支护安全的同时兼具有较明显的经济性,其研究成果有一定的理论与工程实用价值。     

结构模型修正的遗传算法方法研究

讨论实际工程中结构理论模型与实际模型的区别和模型修正的方法,研究遗传算法的基本理论,指出其可用于结构模型的优化修正.将结构振动理论和遗传算法相结合,提出用遗传算法进行结构模型修正的思路和方法,并进行具体实现.最后用一个实例对这一方法进行验证.     

Logit多路径分配模型及其求解算法研究

通过对多路径Logit分配模型及经典的Dail算法的研究,并针对kgit分配模型及Dail算法的缺陷,提出的一种改进的kgit模型及相应改进的Dail算法,对交通分配及速度求解速度都有非常重要的意义。     

基于自适应算法的单矢量传感器抗相干干扰

将矢量传感器组合指向性vs的零点对准已知的相干干扰方向,获得"干净"的目标信号,然后结合自适应算法抵消矢量传感器原始数据中各通道的相干干扰,达到抗相干干扰的目的.文中阐述了方法的原理,进行了多种情况下的仿真,并给出实验结果.仿真和实验结果表明该方法能有效抑制方位已知的相干干扰.     

Power-Aware Anycast Routing in Wireless Sensor Network Exploiting Small World Effect

By considering energy-efficient anycast routing in wireless sensor network (WSN), and combining small world characteristics of WSN with the properties of the ant algorithm, a power-aware anycast routing algorithm (SWPAR) with multi-sink nodes is proposed and evaluated. By SWPAR, the optimal sink node is found and the problem of routing path is effectively solved. Simulation results show that compared with the sink-based anycast routing protocol (SARP) and the hierarchy-based anycast routing protocol (HARP), the proposed algorithm improves network lifetime and reduces power consumption.