Behavior-consistent information-based network traffic control for evacuation operations

The evacuation operations problem aims to avoid or mitigate the potential loss of life in a region threatened or affected by a disaster. It is shaped to a large extent by the evolution of evacuation traffic resulting from the demand–supply interactions of the associated transportation network. Information-based control is a strategic tool for evacuation traffic operations as it can enable greater access to the affected population and more effective response. However, comparatively few studies have focused on the implementation of information-based control in evacuation operations. This study develops a control module for evacuation operations centered on addressing the demand–supply interactions by using behavior-consistent information strategies. These strategies incorporate the likely responses of evacuees to the information provided in the determination of route guidance information. The control module works as an iterative computational process involving an evacuee route choice model and a control model of information strategies to determine the route guidance information to direct evacuation traffic so as to approach a desired network traffic flow pattern. The problem is formulated as a fuzzy logic based optimization framework to explicitly incorporate practical concerns related to information dissemination characteristics and social equity in evacuation operations. Numerical experiments highlight the importance of accounting for the demand–supply interactions, as the use of behavior-consistent information strategies can lead evacuee route choices to approach the operator-desired proportions corresponding to the desired traffic pattern. The results also indicate that while a behavior-consistent information strategy can be effective, gaps with the desired route proportions can exist due to the discrete nature of the linguistic messages and the real-world difficulty in accurately modeling evacuees’ actual route choice behavior.     

隧道瓦斯防突技术探讨

随着国家高速公路的迅猛发展,公路隧道越来越多地应用于高速公路的建设当中。当隧道经过煤层或采空区时,隧道周边围岩就会有瓦斯存在。作为特殊地质地段隧道的一种,瓦斯隧道施工过程中,要特别注意隧道内瓦斯的浓度,否则,极有可能发生瓦斯爆炸,引起工程事故。结合松卜岭隧道的瓦斯防护技术设计,主要讨论隧道通过煤层时,隧道掘进施工过程中的瓦斯突出危险性预测及防突措施。     

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.     

无线技术在汽车电控系统中的应用

为了解决传统汽车中组合开关线束复杂、价格昂贵的问题,设计并搭建了一个基于无线局域网络的电气机构控制系统。选用车载电脑为人车交互窗口来完成人车对话,以新力维无线模块WM001S为载体实现无线控制信号与汽车CAN总线的连接,这样就实现了控制开关与汽车ECU的通信。再通过ECU来实现对电气机构的控制,从而达到了借助无线网络来控制汽车电气机构的目的。实验结果证明,该系统最大响应时间为200ms、操作简单、工作稳定可靠、大大降低了线束的复杂程度以及布置线束的空间要求。     

波浪模型试验应当注意的一些问题

根据实践经验,按照波浪物理模型试验要求、工作大纲、试验条件、制作模型、试验过程和报告编写等环节,总结了容易疏忽的问题,并给出了解决这些问题的方法和建议,以促进模型试验成果的科学性和可靠性,提高工作效率,避免不必要地失误。可供从事此项工作人员特别是经验不多的年轻人借鉴和参考。     

基于元胞理论的船厂码头移泊作业问题算法

为了解决大规模船厂的码头移泊作业问题，基于船舶移动路径具有过程演进的特性，建立了码头移泊作业问题的元胞数学模型。按照问题元胞模型的演进特性和演变规则，采用蚁群智能算法来对模型进行求解，并论证了该算法的收敛性。通过实例计算，其结果与船厂实际操作安排进行比较和分析，验证了该算法的有效性和优越性。     

论述沥青混凝土路面施工质量管理与费用控制

结合工程实例,对完成工程的关键要素进行分析,介绍了沥青混凝土路面施工质量管理与费用控制的经验。     

Evolving competition between Hong Kong and Shenzhen ports

Shenzhen Port (SZP), once a negligible local port, has risen dramatically to a world-leading container port and an “equal” player with Hong Kong Port (HKP). Will this market share reallocation continue, or will equilibrium be eventually realized for HKP to prosper continuously? We examine the relationship between these two ports to answer this question. We propose a new transformation method to describe the growth of container cargo transport demand, define the quantitative measures of the competition relationship and port competitiveness, and present a rigorous analytical framework with econometric tests and models to understand the true relationship between HKP and SZP. Direct empirical tests suggest that SZP complements HKP; however, the two ports exhibit strong competition when the effect of demand growth is excluded. Considering transshipment separately, we find that the impact of SZP on HKP is negative in transshipment but complementary in direct shipment. We may conclude that HKP does not affect SZP, whereas SZP has competitive power over HKP. These results are consistent with the findings of some previous theoretical studies.     

基于GRNN的GSM-R场强覆盖预测算法

在比较Hata模型修正方法和GRNN算法场强覆盖预测效果的基础上,仿真分析了训练集构成和平滑因子选择对GRNN算法预测效果的影响,给出了训练集构成和平滑因子选择的方法;提出了电波传播环境相似系数来表征GRNN模型在不同环境下的适用性。仿真结果表明,两种传播环境的相似系数越大,由一种环境下测试数据确定的GRNN在另一环境下的预测精度越高。     

Asymmetric response model for evaluating airline service quality: An empirical study in cross-strait direct flights

In this paper we propose a framework to investigate service quality asymmetrically. An asymmetric response model within structural equation framework is developed to study the relationship between service quality and the passenger’s behavioral intention in the cross-strait direct flight (Taiwan–Shanghai). The results reveal that service quality in the loss region has more impact on behavioral intention than service quality in the gain region. Hence, attention should be paid to the service quality of important attributes in the loss region and strategies should ensure service quality of those important attributes that meet passenger’s expectations.