Efficient missing data imputing for traffic flow by considering temporal and spatial dependence

The missing data problem remains as a difficulty in a diverse variety of transportation applications, e.g. traffic flow prediction and traffic pattern recognition. To solve this problem, numerous algorithms had been proposed in the last decade to impute the missed data. However, few existing studies had fully used the traffic flow information of neighboring detecting points to improve imputing performance. In this paper, probabilistic principle component analysis (PPCA) based imputing method, which had been proven to be one of the most effective imputing methods without using temporal or spatial dependence, is extended to utilize the information of multiple points. We systematically examine the potential benefits of multi-point data fusion and study the possible influence of measurement time lags. Tests indicate that the hidden temporal–spatial dependence is nonlinear and could be better retrieved by kernel probabilistic principle component analysis (KPPCA) based method rather than PPCA method. Comparison proves that imputing errors can be notably reduced, if temporal–spatial dependence has been appropriately considered.     

The visual impact of development in coastal zone areas

Abstract

The focus of this paper is theoretical, as well as methodological. It reviews previous studies of visual impact and reports research by the author on people's evaluation of the appropriateness of different man‐made facilities in different coastal‐area contexts and other environments. In this study, subjects were asked to react to slides developed through the use of landscape models and experimental facilities to simulate the appearance of a building in the landscape, while systematically varying the visual relatedness between the two. Specific interest centered on the variable of congruity vs. contrast between the appearance of the building and its landscape context, manipulated by co‐varying the attributes of color and size to create a five‐point scale of contrast/obtrusiveness. The hypothesis was that judgments of appropriateness, and to a lesser extent judgments of liking, would vary inversely with level of contrast. The role of two further variables, the functional significance of the building in its setting, and the character of the setting itself, was also investigated. The author reviews methodological issues involved where subjects respond to visual stimuli for purposes of judging change in visual quality. These methodological issues include: stimulus‐selection and problems of simulation, choice of response measures, and choice of respondents, and the treatment of individual differences. The author calls for development of standardized scales and indices such as “perceptually‐relevant environmental quality indicators.”     

Short-term forecasting of high-speed rail demand: A hybrid approach combining ensemble empirical mode decomposition and gray support vector machine with real-world applications in China

Short-term forecasting of high-speed rail (HSR) passenger flow provides daily ridership estimates that account for day-to-day demand variations in the near future (e.g., next week, next month). It is one of the most critical tasks in high-speed passenger rail planning, operational decision-making and dynamic operation adjustment. An accurate short-term HSR demand prediction provides a basis for effective rail revenue management. In this paper, a hybrid short-term demand forecasting approach is developed by combining the ensemble empirical mode decomposition (EEMD) and grey support vector machine (GSVM) models. There are three steps in this hybrid forecasting approach: (i) decompose short-term passenger flow data with noises into a number of intrinsic mode functions (IMFs) and a trend term; (ii) predict each IMF using GSVM calibrated by the particle swarm optimization (PSO); (iii) reconstruct the refined IMF components to produce the final predicted daily HSR passenger flow, where the PSO is also applied to achieve the optimal refactoring combination. This innovative hybrid approach is demonstrated with three typical origin–destination pairs along the Wuhan-Guangzhou HSR in China. Mean absolute percentage errors of the EEMD-GSVM predictions using testing sets are 6.7%, 5.1% and 6.5%, respectively, which are much lower than those of two existing forecasting approaches (support vector machine and autoregressive integrated moving average). Application results indicate that the proposed hybrid forecasting approach performs well in terms of prediction accuracy and is especially suitable for short-term HSR passenger flow forecasting.     

Estimates of vertical mixing during a Lagrangian experiment off the Galician coast

An adjoint 1-D model was used to determine vertical diffusivity coefficients from temperature profiles collected within a filament escaping from the Galician coast following an upwelling event. The optimisation scheme ended with relatively high diffusivity values within the thermocline (9×10⁻⁵ m² s⁻¹). Such high values are relevant for biogeochemical exchanges between surface and deep waters in stratified areas.The optimised values were several orders of magnitude higher than the bulk of diffusivity measurements recorded with a free-falling device; however, the optimisation solution was consistent with the arithmetic mean of the measurements in the thermocline (7.7×10⁻⁵ m² s⁻¹), giving more weight to the few largest values. Below the thermocline, the data assimilation method failed because of the three-dimensional nature of the advective field of the upwelling system. Ignoring this advective forcing in the model led to estimates that were two orders of magnitude too high.The results suggest that turbulent mixing is a random process where a few intense events determine the average mixing that drives the long-term evolution of the water column structure. This statistical property is very important when one wants to use instantaneous diffusivity measurements for modelling purposes.     

二赛线GTM沥青混合料设计

结合内蒙古自治区二连浩特-赛汉塔拉的工程实例,介绍了GTM混合料设计方法的特点,以及根据当地的气候、交通状况确定工程级配范围和室内采用GTM完成混合料的设计及技术性能的检验。     

GTM法在公路沥青路面施工中的应用研究

结合GTM法技术在河北省张石高速公路中的实践应用,介绍GTM法的设计原理、施工工艺和质量控制体系,尤其是对施工过程质量控制点和沥青路面最大密实度标准的研究分析,有效地降低了工程施工费用,提高了路面的服务寿命。     

连续梁桥跨河施工支架研究

主要研究了采用装配式公路钢桥桁架(通常称为贝雷架)做为支架进行连续梁桥现浇箱梁混凝土的施工方法;研究了跨河施工支架的技术方案,特别是施工支架在桥墩上的刚性斜撑,同时结合现场试验研究了施工支架的分析计算方法及变形。研究表明,采用装配式公路钢桥桁架解决跨河预应力混凝土连续梁现浇混凝土施工支架问题是有效的。     

杭州湾跨海大桥高墩区引桥箱梁设计

杭州湾跨海大桥高墩区引桥是连接航道桥和低墩区引桥的桥梁,按其所处位置分为4段,分别是南航道桥南、北引桥和北航道桥南、北引桥,均采用70 m整孔预制吊装的预应力混凝土连续箱梁结构。     

水泥混凝土路面碎石化层应力强度因子有限元分析

为比较是否碎石化对加铺后沥青路面结构应力的影响,本文从断裂力学入手,借助有限元软件,按等参八节点二维平面应变单元分析了两者在沥青加铺层情况相同时层底的应力强度因子。经对比分析,两者的Ⅰ型应力强度因子差别很大,而Ⅱ型应力强度因子基本相同,表明碎石化后沥青加铺层层底具有更好的受力特性,与不破碎直接加铺相比,能显著降低沥青加铺层底反射裂缝的可能性。这表明碎石化工艺对旧水泥混凝土路面的处治能满足加铺要求,达到了工艺处理的目的。     

基于三弯矩样条函数插值模型的非等距时序灰色预测方法

给出了三弯矩样条函数插值模型,用以解决非等距时序GM（1,1）的灰色预测问题.在国际平整度指数IRI的非等距时序样条灰色预测应用实例表明,该方法在作非等距时序列向等距时序列转换中保留了原有数据序列所呈现出的阶段性规律,具有精度高、实用性强的特点.