现代造船对涂装人才的要求及培养方式探讨

文章分析了船舶涂装在现代造船中的地位,结合了我国船舶涂装发展现状,提出了涂装人才培养的要求,探讨了船舶涂装人才培养的方式。     

人口红利结束将促成中国汽车产业消费悬崖(1)

在汽车产业的分析中,可以通过建立人口分析的范式,结合人口因素、人的消费习惯及汽车报废年限来预测汽车产业的发展方向。本文从人口结构的角度分析了未来我国汽车产业面临的消费悬崖,并从人口的角度对2001~2010年我国汽车产业的发展及未来老龄化对汽车产业的冲击进行了分析,并提出了我国汽车产业管理要从重视量的扩张向强调质的提升转变。     

汽车电磁兼容的智能预测方法

目前,汽车上应用的电子产品日益增多,用来连接这些电子产品和控制器与电源的线束也越来越复杂,所有这些控制器设备、电源、线束以及总线之间产生电磁干扰的可能性增加,潜在的危害性也逐渐加大。因此,电磁兼容技术越来越受到人们的重视。文章首先介绍了国内外汽车电子兼容技术研究的发展状况,然后详细介绍2种基于人工智能技术来预测电磁兼容性的方法,最后经过分析和比较得出采用智能技术来预测电磁兼容性是有效可行的。     

基于TDM的出租车供需调控方案研究

交通需求管理（TDM）是能从根本上解决城市交通问题的策略,具有现实的意义。针对成都市出租车供需现状,运用系统的思想对各供需调控方案进行评价比选,分析交通需求管理的必要性并提出针对出租车的交通需求管理的具体措施,可为解决出租车的供需矛盾提供参考。     

基于GRNN神经网络的长江干线港口集装箱吞吐量预测

在长江集装箱货源市场调查分析的基础上,根据长江干线集装箱发展形势,结合长江干线港口发展情况及历年数据调查,考虑影响港口吞吐量预测的复杂因素,运用GRNN神经网络的优点,构建预测模型。预测结果证明,该模型在应用中是有效的,且当样本数据短缺时,预测效果也较佳。     

Forecasting demand for high speed rail

It is sometimes argued that standard state-of-practice logit-based models cannot forecast the demand for substantially reduced travel times, for instance due to High Speed Rail (HSR). The present paper investigates this issue by reviewing the literature on travel time elasticities for long distance rail travel and comparing these with elasticities observed when new HSR lines have opened. This paper also validates the Swedish long distance model, Sampers, and its forecast demand for a proposed new HSR, using aggregate data revealing how the air–rail modal split varies with the difference in generalized travel time between rail and air. The Sampers long distance model is also compared to a newly developed model applying Box–Cox transformations. The paper contributes to the empirical literature on long distance travel, long distance elasticities and HSR passenger demand forecasts. Results indicate that the Sampers model is indeed able to predict the demand for HSR reasonably well. The new non-linear model has even better model fit and also slightly higher elasticities.     

A GIS‐based traffic analysis zone design: implementation and evaluation

The purpose of this paper is to implement an efficient method for GIS‐based traffic analysis zone (TAZ) design in order to evaluate and validate such a method. The method was developed by the authors.

Moran's I spatial autocorrelation coefficient and sample variance are used for evaluating the generated TAZs using the Champaign‐Urbana, IL region as a case study. Sensitivity analysis is also conducted to explore the fluctuations in TAZ generation outcomes. The evaluation, the validation as well as the TAZ design have been implemented with ARC/INFO GIS software on a UNIX workstation platform.     

A multi-commodity Lighthill–Whitham–Richards model of lane-changing traffic flow

Systematic lane changes can seriously deteriorate traffic safety and efficiency inside lane-drop, merge, and other bottleneck areas. In our previous studies (Jin, 2010a, Jin, 2010b), a phenomenological model of lane-changing traffic flow was proposed, calibrated, and analyzed based on a new concept of lane-changing intensity. In this study, we further consider weaving and non-weaving vehicles as two commodities and develop a multi-commodity, behavioral Lighthill–Whitham–Richards (LWR) model of lane-changing traffic flow. Based on a macroscopic model of lane-changing behaviors, we derive a fundamental diagram with parameters determined by car-following and lane-changing characteristics as well as road geometry and traffic composition. We further calibrate and validate fundamental diagrams corresponding to a triangular car-following fundamental diagram with NGSIM data. We introduce an entropy condition for the multi-commodity LWR model and solve the Riemann problem inside a homogeneous lane-changing area. From the Riemann solutions, we derive a flux function in terms of traffic demand and supply. Then we apply the model to study lane-changing traffic dynamics inside a lane-drop area and show that the smoothing effect of HOV lanes is consistent with observations in existing studies. The new theory of lane-changing traffic flow can be readily incorporated into Cell Transmission Model, and this study could lead to better strategies for mitigating bottleneck effects of lane-changing traffic flow.     

散货船运输市场周期性分析与预测

国际散货船航运市场在国际航运市场中占有举足轻重的地位,其走势具有周期性,可以预测船舶航运市场的整体趋势,进一步对全球经济形势分析预测。通过对克拉克森报告进行分析和调研,根据调研结果并结合新冠疫情影响确定了散货船航运市场的主要影响因素,采用相关股票指数和数据对各影响因素量化,对历史数据建立时滞模型并进行多元回归分析,进而建立时滞回归模型,构造了代价函数并采用梯度下降法建立多变量线性回归模型,得出表征散货船市场情况的波罗的海指数(BDI)与影响其走势的几种主要因素之间的代数关系,从而用近几年各影响因素的值来预测未来几个月内波罗的海指数的发展趋势,为船市的进一步布局规划提供参考。     

Real-time bus route state forecasting using particle filter and mesoscopic modeling

In the absence of system control strategies, it is common to observe bus bunching in transit operations. A transit operator would benefit from an accurate forecast of bus operations in order to control the system before it becomes too disrupted to be restored to a stable condition. To accomplish this, we present a general bus prediction framework. This framework relies on a stochastic and event-based bus operation model that provides sets of possible bus trajectories based on the observation of current bus positions, available via global positioning system (GPS) data. The median of the set of possible trajectories, called a particle, is used as the prediction. In particular, this enables the anticipation of irregularities between buses. Several bus models are proposed depending on the dwell and inter-stop running time representations. These models are calibrated and applied to a real case study thanks to the high quality data provided by TriMet (the Portland, Oregon, USA transit district). Predictions are finally evaluated by an a posteriori comparison with the real trajectories. The results highlight that only bus models accounting for the bus load can provide valid forecasts of a bus route over a large prediction horizon, especially for headway variations. Accounting for traffic signal timings and actual traffic flows does not significantly improves the prediction. Such a framework paves the way for further development of refined dynamic control strategies for bus operations.