NGI研发策略与单层用户数据交换平台体系结构

以四川省网络通信技术重点实验室有关NGI(下一代因特网)体系结构及相关技术研究为背景,较全面地探讨了NGI研发策略及与NGI体系结构相关的问题.重点是实验室有关NGI的研究:“骨干通信子网优先,外延次之(BSF-OES)”的NGI研发策略;骨干通信子网的单层用户数据交换平台体系结构(SUPA);面向以太网的物理帧时槽交换( EPFTS)技术;未来的开放式网络与应用服务模型(ONASM).还讨论了基于SUPANET(单层用户数据交换平台体系结构网络)框架如何迎接Intemet面临的高速交换、服务质量保障、网络安全和移动性问题的挑战和实现NGI目标的相关问题.     

双电机混合动力车辆串并联驱动模式切换控制方法

为实现双电机混联构型混合动力车辆(HEV)的串并联切换控制,通过对双电机混联构型进行串并联驱动模式分析,提出一种通过三动力源协调控制的无动力中断切换方法.将串联到并联切换过程分为发动机工作点转移、离合器结合、动力源切换3个阶段,将并联到串联行驶切换过程划分为动力源切换、离合器打开、发动机工作点转移3个阶段,并通过仿真分...     

Valuing cargo flexibility in oil transportation

The seaborne oil transportation market is served by two main types of vessels—crude oil tankers and product tankers. Product tankers are designed to move refined oil products, yet they can also opportunistically carry ‘dirty’ products such as crude and heavy fuel oil, subject to the cost of tank cleaning when re-entering the clean products trade. We apply an entry-exit real option model with a stochastic freight rate differential to derive optimal triggers for switching between the two cargo types and estimate the value of the switching option. We show that the value of active switching has grown over time, and generally exceeds the additional construction cost of a product tanker. Our findings are important both from a practical point of view and for our understanding of market integration in the tanker freight market. Specifically, shipowners can use our model as a basis for optimizing chartering policy for clean product tankers. We also show that there are periods where the dirty market is persistently stronger, and discuss the possible reasons for such apparent inefficiencies.     

Decision tree method for modeling travel mode switching in a dynamic behavioral process

As road congestion is exacerbated in most metropolitan areas, many transportation policies and planning strategies try to nudge travelers to switch to other more sustainable modes of transportation. In order to better analyze these strategies, there is a need to accurately model travelers’ mode-switching behavior. In this paper, a popular artificial intelligence approach, the decision tree (DT), is used to explore the underlying rules of travelers’ switching decisions between two modes under a proposed framework of dynamic mode searching and switching. An effective and practical method for a mode-switching DT induction is proposed. A loss matrix is introduced to handle class imbalance issues. Important factors and their relative importance are analyzed through information gains and feature selections. Household Travel Survey data are used to implement and validate the proposed DT induction method. Through comparison with logit models, the improved prediction ability of the DT models is demonstrated.     

舰艇开关电源的低频传导干扰建模与仿真

开关电源的电磁干扰是舰艇电磁兼容工程中的典型问题.针对舰艇电网上出现的低频传导干扰现象,着重探讨开关电源低频传导发射及其对电网的影响.详细分析了开关电源低频传导干扰的形成机理,并为开关电源建立了低频传导发射模型以计算电网上的低频谐波干扰.在此基础上,借助软件工具对开关电源的低频传导干扰进行模拟仿真,分析了流回到电源线上的传导发射电流以及谐波畸变情况,从而实现对开关电源低频传导干扰的数值预测.     

一种单级的高功率因数开关变换器

提出一种新的高功率因数的开关变换器,该变换器采用单级结构,单一占空比ＰＷＭ控制模式,完成功率因校正和输出电压调节双重功能;并对该变换器的工作过程进行了详细分析;最后给出该变换器在电子镇流器电路中的应用。     

中海工业面对后危机时代的修船转型升级

文章根据竞争学和战略管理理论,结合中海工业的实际,分析了金融危机对修船业的宏观影响,解剖了企业微观存在的一些结构性问题,阐明了修船企业应对危机必须在转型升级中解题和破题的观点。     

一种光伏逆变器的多输出辅助开关电源设计

本文设计了一种光伏逆变器的辅助开关电源。由于光伏逆变器需要的辅助电源路数很多,且要考虑高、低压的隔离,所以设计了两个反激式开关电源。文中介绍了这两个开关电源的计算和设计过程,重点论述了变压器磁芯及绕组的设计、反馈及稳压电路的设计。设计的辅助电源已经用于光伏逆变器上,运行稳定可靠。良好的实验结果证明了设计方法的正确性。     

路网规模对出行者路径选择转换的影响

为预测交通流的演化动态,提高交通系统运行效率,需研究路网规模与出行者路径选择转换行为间的关系。首先设计并实施实验室行为实验,收集出行者实际路径选择相关数据。行为实验涉及4个不同规模的虚拟道路网络,30名参与者基于以往的出行信息（即出行时间）在虚拟路网上进行路径选择。然后利用假设检验、回归分析等统计方法对收集到的实验数据进行分析。分析结果表明：随着路网规模的增大,路网达到用户均衡（User Equilibrium, UE）状态的次数减少。对各路网用户均衡状态与系统最优（System Optimum, SO）状态的对比表明：各路径流量的平均值都很接近于UE值,而与SO值相差较大。从逐日路径流量演化和个体选择可变性两方面分析了路网规模与路径选择转换间的关系,发现逐日路径选择转换人数（或个体路径选择转换数量）与路网规模呈正线性相关。此外,个体路径选择转换频率与平均经验出行时间显著相关。由此得出结论：单方面扩大路网规模并不总能促进路网交通流演化到用户均衡状态,且出行时间与个体路径选择转换数量存在幂函数关系。     

An investigation on the performances of mode shift models in transit ridership forecasting

This paper aims at investigating the over-prediction of public transit ridership by traditional mode choice models estimated using revealed preference data. Five different types of models are estimated and analysed, namely a traditional Revealed Preference (RP) data-based mode choice model, a hybrid mode choice model with a latent variable, a Stated Preference (SP) data-based mode switching model, a joint RP/SP mode switching model, and a hybrid mode switching model with a latent variable. A comparison of the RP data-based mode choice model with the mode choice models including a latent variable showed that the inclusion of behavioural factors (especially habit formation) significantly improved the models. The SP data-based mode switching models elucidated the reasons why traditional models tend to over-predict transit ridership by revealing the role played by different transit level-of-service attributes and their relative importance to mode switching decisions. The results showed that traditional attributes (e.g. travel cost and time) are of lower importance to mode switching behaviour than behavioural factors (e.g. habit formation towards car driving) and other transit service design attributes (e.g. crowding level, number of transfers, and schedule delays). The findings of this study provide general guidelines for developing a variety of transit ridership forecasting models depending on the availability of data and the experience of the planner.