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降雨作为一种常见的气象条件,对高速公路网行程时间的稳定性有着直接的影响.本文针对雨天能见度降低、路面摩擦系数变小的特征,通过分析降雨的空间分布模式,建立了雨天路段单元自由流车速、通行能力以及公路网需求水平的修正模型,进而提出了雨天路段单元的广义行程时间函数.结合用户最优平衡分配模型,以及系统工程中的串并联理论,建立了雨天高速公路路段单元、路径、OD对和公路网的行程时间可靠度评价模型.应用Matlab工具箱模拟公路网上的降雨分布,设计了基于Monte Carlo方法的评价模型求解思路.最后以算例验证了该方法在行程时间可靠性评价中的应用.结果表明,能藉此有效地找出雨天公路网中行程时间敏感性最大的关键路段.     

基于液体芯片-飞行时间质谱分析的肺结核患者血清差异表达蛋白

目的应用液体芯片-飞行时间质谱技术分析肺结核患者和正常对照人群的血清蛋白多肽图谱,找出组间具有统计学意义的差异表达蛋白多肽,从而筛选出肺结核的标志蛋白多肽峰图(m/z)。方法应用2种液体蛋白芯片技术(MB-WCX和MB-IMAC-CU)结合飞行时间质谱(MALDI-TOF-MS)对14例病理确诊的肺结核患者和32例正常对照人群进行血清蛋白多肽图谱分析;采用ClinProTools软件分析肺结核患者和正常对照组的组间差异表达蛋白。结果 MB-WCX型液体蛋白芯片处理后共获得74个蛋白多肽峰图,其中42个蛋白多肽峰图呈组间极显著差异(P<0.001)表达。MB-IMAC-CU型液体蛋白芯片处理后共获得68个蛋白多肽峰图,有11个蛋白多肽呈组间极显著差异(P<0.001)表达,且其中的8个峰图与MB-WCX型液体芯片检出的组间极显著差异峰图完全相同。经MB-WCX处理所获的42个差异蛋白多肽峰图中有17个蛋白多肽在肺结核患者组中表达上调,其余25个蛋白多肽在肺结核患者组中表达下调。结论利用液体芯片-飞行时间质谱技术可以从肺结核患者的血清中获得稳定丰富的蛋白多肽图谱,并且能够筛选出潜在的疾病标志物。     

基于非等时序灰色模型的路基沉降预测

结合高速公路路基施工沉降观测数据,讨论了灰色系统理论和双曲线模型在公路路基沉降预测中的应用,并对等间隔的灰色模型GM(1,1)进行了改进,建立了任意时间间隔的非等时序改进灰色模型。通过具体工程实践,给出了灰色模型和双曲线模型对公路路基沉降量预测结果与实测结果的比较,结果表明灰色模型的预测沉降量与实际沉降量更接近,精度更高,更能满足工程需要。     

基于径向基函数神经网络的城市道路路段行程时间实时预测模型

提出利用径向基函数（RBF）神经网络方法对城市道路路段行程时间进行建模NN,并结合线圈和视频实测数据进行仿真分析,以实际行程时间和模型输出的行程时间预测值比较验证了模型的合理性。并将RBF神经网络方法与BP神经网络方法进行比较,结果表明RBF神经网络相对于BP神经网络训练时间短,且预测精度更高。     

连续刚构桥施工阶段地震响应分析研究

为研究不同地震作用对大跨连续刚构桥建造过程中不同施工阶段的响应,结合新颁布的公路桥梁抗震设计细则,以南宁仙葫大桥为例建有限元模型,采用反应谱法及动态时程分析方法,输入不同烈度的地震作用,对采用悬臂法施工的不同施工阶段的地震响应进行分析对比,结果表明连续刚构桥建造过程中悬臂端位移、主梁根部弯矩及桥墩底部弯矩变化较大,研究结果可以对大跨度连续刚构桥的动力特性以及地震反应特性有更深入的了解。     

海上舰艇编队高精度时间同步系统设计

针对舰艇编队遂行协同打击任务的高精度时统需求,提出一种超宽带CDMA体制的时统系统设计方案。该系统应用TOA算法,基于超宽带高时间分辨率波形设计,采用可靠同步、干扰抑制和FFT校频等关键算法,实现复杂电磁环境下作战节点快速移动中可靠高精度时间统一,时间同步精度达10 ns。关键算法仿真和试验样机测试证明该系统设计和关键算法合理有效。     

Embedding risk attitude and decision weights in non-linear logit to accommodate time variability in the value of expected travel time savings

In recent years we have seen important extensions of logit models in behavioural research such as incorporation of preference and scale heterogeneity, attribute processing heuristics, and estimation of willingness to pay (WTP) in WTP space. With rare exception, however, a non-linear treatment of the parameter set to allow for behavioural reality, such as embedded risk attitude and perceptual conditioning of occurrence probabilities attached to specific attributes, is absent. This is especially relevant to the recent focus in travel behaviour research on identifying the willingness to pay for reduced travel time variability, which is the source of estimates of the value of trip reliability that has been shown to take on an increasingly important role in project appraisal. This paper incorporates, in a generalised non-linear (in parameters) logit model, alternative functional forms for perceptual conditioning (known as probability weighting) and risk attitude in the utility function to account for travel time variability, and then derives an empirical estimate of the willingness to pay for trip time variability-embedded travel time savings as an alternative to separate estimates of time savings and trip time reliability. We illustrate the richness of the approach using a stated choice data set for commuter choice between unlabelled attribute packages. Statistically significant risk attitude parameters and parameters underlying decision weights are estimated for multinomial logit and mixed multinomial logit models, along with values of expected travel time savings.     

A bayesian dynamic linear model approach for real-time short-term freeway travel time prediction

This paper presents a Bayesian inference-based dynamic linear model (DLM) to predict online short-term travel time on a freeway stretch. The proposed method considers the predicted freeway travel time as the sum of the median of historical travel times, time-varying random variations in travel time, and a model evolution error, where the median is employed to recognize the primary travel time pattern while the variation captures unexpected supply (i.e. capacity) reduction and demand fluctuations. Bayesian forecasting is a learning process that revises sequentially the state of a priori knowledge of travel time based on newly available information. The prediction result is a posterior travel time distribution that can be employed to generate a single-value (typically but not necessarily the mean) travel time as well as a confidence interval representing the uncertainty of travel time prediction. To better track travel time fluctuations during non-recurrent congestion due to unforeseen events (e.g., incidents, accidents, or bad weather), the DLM is integrated into an adaptive control framework that can automatically learn and adjust the system evolution noise level. The experiment results based on the real loop detector data of an I-66 segment in Northern Virginia suggest that the proposed method is able to provide accurate and reliable travel time prediction under both recurrent and non-recurrent traffic conditions.     

Bus arrival time prediction at bus stop with multiple routes

Provision of accurate bus arrival information is vital to passengers for reducing their anxieties and waiting times at bus stop. This paper proposes models to predict bus arrival times at the same bus stop but with different routes. In the proposed models, bus running times of multiple routes are used for predicting the bus arrival time of each of these bus routes. Several methods, which include support vector machine (SVM), artificial neural network (ANN), k nearest neighbours algorithm (k-NN) and linear regression (LR), are adopted for the bus arrival time prediction. Observation surveys are conducted to collect bus running and arrival time data for validation of the proposed models. The results show that the proposed models are more accurate than the models based on the bus running times of single route. Moreover, it is found that the SVM model performs the best among the four proposed models for predicting the bus arrival times at bus stop with multiple routes.     

舰船气泡尾流特性的数值模拟和实验研究

文章基于N-S方程,并结合两相流的相关模型,数值模拟了双桨实船气泡尾流。通过海水中气体含量的变化情况,分析了尾流气泡产生、增大、破碎和消失等过程。得到了近场扩散区和远场尾流区中含气量的空间、时间分布特性。研究结果表明,近场尾流区中海水含气量基本以乘幂格式衰减,而在远场尾流区,则与指数衰减格式符合得较好。用光学的方法模拟测量了舰船尾流的衰减规律,实验结果与文中的理论数值结果一致。