基于偏最小二乘回归的疏浚产量预测方法

针对绞吸式挖泥船产量预测困难的问题,对挖泥船作业实时反馈的数据进行研究。利用Relief权重算法提取出影响挖泥船产量的主要工艺参量,并在此基础上采用偏最小二乘回归,建立主要工艺参量与产量之间的数学模型,实现对挖泥船产量的预测。结果表明,利用偏最小二乘回归建立的数学模型能够很好地对挖泥船的产量进行预测,可为预测挖泥船的产量提供一种有效的方法。     

Assessment of factors associated with travel time reliability and prediction: an empirical analysis using probabilistic reasoning approach

Significant efforts have been made in modeling a travel time distribution and establishing measures of travel time reliability (TTR). However, the literature on evaluating the factors affecting TTR is not well established. Accordingly, this paper presents an empirical analysis to determine potential factors that are associated with TTR. This study mainly applies the Bayesian Networks model to assess the probabilistic association between road geometry, traffic data, and TTR. The results from this model reveal that land use characteristics, intersection factors, and posted speed limits are directly associated with TTR. Evaluating the strength of the association between TTR and the directly related variables, the log odds ratio analysis indicates that the land use factor has the highest impact (0.83) followed by the intersection factor (0.57). The findings from this study can provide valuable resources to planners and traffic operators in their decision-making to improve TTR with quantitative evidence.     

废食用油预脱硫胶粉改性沥青组分与黏弹性研究（双语出版）

为研究废食用油预脱硫胶粉（WRO）对沥青组分及黏弹性的影响,在不同掺量、加工温度和加工时间下分别制备了15组废食用油预脱硫胶粉改性沥青（WROMA）。基于四组分试验、DSR时间扫描试验、多应力蠕变回复试验分析了沥青组分及黏弹性变化的规律。结果表明：在组分方面,WRO中的橡胶烃主要补充沥青质,油分大部分补充饱和分,少部分补充芳香分;加工工艺与改性沥青中饱和分和胶质的含量线性相关性较弱,与芳香分及沥青质的含量线性相关性很强,且芳香分与沥青质含量主要受WRO掺量影响。在黏弹性方面,WRO掺量增加,改性沥青高温黏性降低,弹性增加。为保证改性沥青获得足够的高温弹性,WRO最佳掺量为30%,加工温度为160℃、加工时间为2 h。综合组分与黏弹性的分析结果可知：芳香分是影响WROMA高温黏性的主导因素,其含量越高沥青黏性越明显;沥青质和WRO中的橡胶烃是影响WROMA高温弹性的主导因素,两者含量越高,改性沥青弹性越明显。     

基于HMM-SVR的船舶动力设备故障模式识别与状态预测研究

船舶动力设备因故障监测信号样本少、变化缓慢且数据特征呈非线性,使得设备故障模式的准确识别和状态预测比较难。鉴于此,文章研究了基于隐马尔科夫模型的故障模式识别方法,利用该模型将微弱变化的信号特征转换为变化较大的对数似然概率对故障模式实现有效识别。在此基础上进一步提出基于HMM-SVR的设备状态预测模型,将遗传算法用于支持向量回归模型参数寻优,并结合隐马尔科夫模型,实现对设备状态的预测。对船用柴油机进行仿真,结果表明上述模型具有较高的识别率,能准确预测船舶动力设备的当前状态。     

Soil Body Deformation Caused by Construction of a Double-Line Shield Tunnel with Multiple Factors北大核心CSCD

Considering the influence of many factors (soil loss, frontal additional thrust, the friction force of the shield shell and the additional grouting force), a method for improving the uniform soil body movement model is pro-posed, and a mechanical calculation model is established to study the calculation method for soil body deformation caused by double-line parallel shield driving. Based on the Mindlin solutions of elastic mechanics, the theoretical solutions for soil body deformations caused by the last three factors are calculated; considering the uniform soil body movement model, the theoretical solutions for soil body deformations caused by soil loss are calculated, then the to-tal theoretical solutions for soil body deformations under multiple factors are obtained by means of superposition. The vertical surface settlement, vertical horizontal displacement, and vertical displacements of the soil body at different depths of Hangzhou Metro Line 1 are calculated to analyze the variation laws. Meanwhile the influential factors for horizontal displacement variation are studied. The research shows that with a change of depth, the settlement of the soil body changes within the scope of 10 to 13 m in the horizontal direction near where the maximum settlement occurs;the direction of the horizontal displacement of the soil body changes with a change of the positional relationship be-tween the calculation points and the tunnel; and with an increase of interval J for the two tunnels, the horizontal dis-placement of the soil body of a deep double-line tunnel decreases while the displacement near the surface changes slightly. © 2018, Editorial Office of "Modern Tunnelling Technology". All right reserved.     

Assessing the impact of reduced visibility on traffic crash risk using microscopic data and surrogate safety measures

Due to the difficulty of obtaining accurate real-time visibility and vehicle based traffic data at the same time, there are only few research studies that addressed the impact of reduced visibility on traffic crash risk. This research was conducted based on a new visibility detection system by mounting visibility sensor arrays combined with adaptive learning modules to provide more accurate visibility detections. The vehicle-based detector, Wavetronix SmartSensor HD, was installed at the same place to collect traffic data. Reduced visibility due to fog were selected and analyzed by comparing them with clear cases to identify the differences based on several surrogate measures of safety under different visibility classes. Moreover, vehicles were divided into different types and the vehicles in different lanes were compared in order to identify whether the impact of reduced visibility due to fog on traffic crash risk varies depending on vehicle types and lanes. Log-Inverse Gaussian regression modeling was then applied to explore the relationship between time to collision and visibility together with other traffic parameters. Based on the accurate visibility and traffic data collected by the new visibility and traffic detection system, it was concluded that reduced visibility would significantly increase the traffic crash risk especially rear-end crashes and the impact on crash risk was different for different vehicle types and for different lanes. The results would be helpful to understand the change in traffic crash risk and crash contributing factors under fog conditions. We suggest implementing the algorithms in real-time and augmenting it with ITS measures such as VSL and DMS to reduce crash risk.     

Long-term impact of the Shinkansen on rail and air demand: analysis with data from Northeast Japan

This paper analyses how the high-speed rail construction in Northeast Japan (Tohoku) has affected total demand and interregional travel patterns. We use annual interregional passenger data from 1989 to 2012 and apply regression analysis with the demand between Tokyo and the Tohoku prefectures as the dependent variable. We distinguish particularly between the ‘Full-’ and the ‘Mini-’ Shinkansen, where the latter are branch services running with reduced speed. We find that the ‘Full-Shinkansen’ quickly increases rail and total public transport trips and generates additional rail demand year on year. The ‘Mini-Shinkansen’ impacts are less pronounced. Furthermore, our analysis shows that the Shinkansen has shifted some demand from air to rail once it started operation and increased rail share gradually. We therefore suggest that predictions of demand impacts should carefully distinguish immediate from gradual impacts. We also discuss differences in regional demand in that not all prefectures have gained equally from Shinkansen construction.     

复合动力超长续航无人艇系统的设计与实现

为实现无人艇在海上追踪、搜救、巡逻、反潜等任务中的超长续航,避免因油料限制而被迫任务中断,设计了一套以风能、太阳能为动力的无人艇系统,利用风帆为无人艇推进,太阳能为船上电控设备提供电能。该系统由无人艇和岸基监控平台组成,无人艇可通过python开发的数据采集模块和算法模块实时采集环境数据、计算、生成并下达控制指令,在风区内可超长续航自主航行,实现全风向利用;岸基监控平台可实时监控无人艇状态,并进行自主/遥控模式切换。对系统进行了测试,通讯连接试验的可靠性高;无人艇航行试验验证了全风向自主航行的可行性,运行轨迹与仿真结果基本重合;太阳能供电分析理论上验证了风区超长续航的可实现性。     

基于粒子群算法的水下多元线阵阵形有源校正方法

针对存在阵元位置误差的水下多元线阵,提出一种基于粒子群优化算法的远场有源阵形校正方法.该方法选用2个辅助源分时工作方式,利用无条件最大似然方位估计算法构建目标函数,并通过粒子群算法对阵元位置进行寻优.利用该方法对均匀线阵进行性能仿真实验.结果表明:该方法稳健性好、校正精度高,具有一定的应用前景.