基于Hopfield神经网络的雷达多目标跟踪

针对海上船舶雷达在多目标跟踪过程中实时性较差和不能快速响应的问题,提出目前密集杂波情况下多目标跟踪中最为有效的数据关联算法——联合概率数据关联(Joint Probabilistic Data Association,JPDA)算法。为解决JPDA随着目标增多的情况会出现的组合“爆炸”及计算量较大导致跟踪实时性较差的问题,从分析联合概率数据关联确认矩阵着手,依据Hopfield神经网络在解决旅行商问题(Travelling Salesman Problem,TSP)时的思路,提出基于Hopfield神经网络联合概率数据关联(Hopfield Neural Network Joint Probability Data Association,H-JPDA)来改进联合概率数据关联算法,通过简化矩阵拆分过程,显著减少计算量,提高跟踪的实时性。基于上述改进的神经网络联合概率数据关联算法,通过MATLAB对多目标跟踪进行仿真,仿真结果表明该算法能提高跟踪的实时性和快速响应能力。     

城市轨道交通站点数据链客流预测方法研究

城市轨道交通客流预测数据是城市轨道交通设计与运营的重要依据与基础,在总结分析我国城市轨道交通客流预测经验及研究成果的基础上,提出基于城市土地利用法的站点数据链客流预测方法,系统介绍该预测方法的理论体系,并以杭州地铁4号线为例,验证站点数据链客流预测方法的科学性与合理性,以期使该预测方法在客流预测与校核中具有指导意义。     

冲压车间生产管理系统分析及设计

分析了整车制造业企业冲压车间业务点及生产方式,针对生产线之间相互独立、缺乏数据传递,而导致形成信息孤岛问题,设计了基于面向制造企业车间执行层的生产信息化管理制造执行系统(MES),设计开发了MES实时数据监测系统。使用被动扫描式实现现场设备状态的实时采集。用户可以通过PC浏览器远程监测现场设备的工作状态。MES实时数据监测系统开发成本低、运行稳定且维护简便,可以替代传统岗位式监测方式,具有较高的研究和市场应用价值。     

物流无人机对地风险评估方法研究

随着智能交通运输体系的完善和无人机应用场景的拓展，物流无人机应运而生。物流无人机被认为是解决快递配送“最后一公里”问题的有效运输方式，但由空中碰撞、系统失效等原因导致的无人机坠落有可能对地面人员造成伤害并产生经济损失。因此本文聚焦无人机物流运输场景，研究物流无人机坠地后造成的死亡人数和经济损失，并利用风险矩阵综合评估风险。主要内容包括：分析物流无人机空中碰撞后产生机货分离的情况，建立由物流无人机和货物坠地造成 的地面死亡人数计算模型；对无人机和货物进行分类，建立经济损失计算模型，包括由无人机和货物价值损失构成的直接经济损失，以及由社会服务机构费用消耗构成的间接经济损失；综合物 流无人机和货物坠地造成的地面死亡人数和经济损失建立风险评估矩阵。算例证明，利用本文方法得到的地面死亡人数为每飞行小时3.74×10-12~1.87×10-7人，符合等效安全水平；每次事故经济损失为6734.8~33619.0元，也在合理区间内。本文提供的方法可以对物流无人机地面风险评估和管控提供一定借鉴和指导意义。     

数据采集算法的研究

介绍利用C#编程制作数据采集软件的方法,讨论该软件在工程中的应用情况.数据采集软件利用以太网协议读取PLC中的数据,并将现场设备信息存储到数据库中,以实现对PLC采集数据的自动计算,节省人力,缩短项目开发周期.     

Not bored yet - Revisiting respondent fatigue in stated choice experiments

Stated choice surveys are used extensively in the study of choice behaviour across many different areas of research, notably in transport. One of their main characteristics in comparison with most types of revealed preference (RP) surveys is the ability to capture behaviour by the same respondent under varying choice scenarios. While this ability to capture multiple choices is generally seen as an advantage, there is a certain amount of unease about survey length. The precise definition about what constitutes a large number of choice tasks however varies across disciplines, and it is not uncommon to see surveys with up to twenty tasks per respondent in some areas. The argument against this practice has always been one of reducing respondent engagement, which could be interpreted as a result of fatigue or boredom, with frequent reference to the findings of Bradley and Daly (1994) who showed a significant drop in utility scale, i.e. an increase in error, as a respondent moved from one choice experiment to the next, an effect they related to respondent fatigue. While the work by Bradley and Daly has become a standard reference in this context, it should be recognised that not only was the fatigue part of the work based on a single dataset, but the state-of-the-art and the state-of-practice in stated choice survey design and implementation has moved on significantly since their study. In this paper, we review other literature and present a more comprehensive study investigating evidence of respondent fatigue across a larger number of different surveys. Using a comprehensive testing framework employing both Logit and mixed Logit structures, we provide strong evidence that the concerns about fatigue in the literature are possibly overstated, with no clear decreasing trend in scale across choice tasks in any of our studies. For the data sets tested, we find that accommodating any scale heterogeneity has little or no impact on substantive model results, that the role of constants generally decreases as the survey progresses, and that there is evidence of significant attribute level (as opposed to scale) heterogeneity across choice tasks.     

基础设施公私合营模式融资影响因素及空间溢出效应研究

在城市层面，影响基础设施PPP(公私合营模式)项目融资额的因素具有多样性。本文基于 2015—2017年我国地级市面板数据，采用空间回归模型对地级市基础设施PPP项目融资额的影 响因素进行实证分析，并验证了PPP项目融资额在空间层面具有溢出效应。研究结果表明：空间 误差模型相比混合OLS回归模型，对于分析PPP项目融资额影响因素的拟合效果更好；PPP项目 融资额在城市层面上具有显著的正向空间溢出效应，即一个城市PPP项目融资额更容易受到相 邻城市PPP项目融资额的影响。地方政府财政缺口、地区生产总值、固定资产投资额、人口密度 对PPP项目融资额虽然都具有显著相关关系，但在不同地区间影响的差异性较大。地方政府财 政缺口在中东部城市与PPP项目融资额呈现显著正相关，即地方政府财政缺口越大，城市越倾向 于采用PPP模式进行基础设施投融资；而在西部城市，两者间这种相关关系则不显著。     

不规则物流园区功能区块布局模型与算法

物流园区功能区块的合理布局对于降低物流成本、提高物流作业效率有重要意义.传统的研究主要建立在假定物流园区是矩形的理想情况下,本文基于栅格数据结构,构建了以运输成本最小为目标的不规则物流园区功能区块布局的集合划分模型,并引入了栅格图像矢量化技术,用于提取布局形成后的图像拓扑结构,获得路网信息,然后设计了基于割树技术的变邻域搜索算法进行求解.最后以某物流园区为例,通过MATLAB编程计算得出布局方案,验证了本文模型和算法的有效性.     

基于船舶大数据的港口装卸效率值计算方法

集装箱港口的装卸效率是衡量港口竞争力和吸引船公司前来挂靠的关键指标之一。为准确估计港口的装卸效率值，基于船舶自动识别系统(AIS)数据，利用 Greatmaps(GMap)可视化技术，提出一种计算港口装卸效率值的方法。利用该方法估算上海港、新加坡港、深圳港和宁波-舟山港的月度装卸效率值，4 个港口 2017 年上半年的装卸效率月度均值分别为 2.85、1.87、2.17 和 2.10。基于上半年估计的装卸效率值，对4个港口下半年的月度吞吐量进行估计，估算误差均值分别为2.77%、2.06%、2.93%和2.46%。结果表明，该方法能够较为准确地反映港口的装卸效率，可应用于推断和实时监控港口的吞吐量，为港口提高绩效和船公司选择港口策略提供理论参考，提升港口数字化管理水平。     

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.