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针对航班延误难以预测的问题,采用支持向量机回归方法建立航班到港延误预测模型。首先,采用相空间重构理论计算到港延误的延迟时间、嵌入维数和最大Lyapunov指数,发现到港延误时间序列存在混沌特性;将航班到港延误时间序列进行相空间重构,并结合执飞该航班的航空器在上游机场的离港延误构建模型的输入向量;其次,将粒子群算法、差分进化算法和遗传算法进行比较,用于选择最优的模型参数,实验表明,差分进化算法能够以较高概率获得最优的预测模型;最后,比较该模型、单一因素预测模型和相关向量机预测模型的航班延误预测性能。结果表明,该模型的预测性能明显优于另外两种模型,能够有效预测航班延误。     

城市居住区停车配建标准研究

为了解决居住区的停车问题,更好地规范停车供给、促进居住区动静态交通的协调,通过调查与分析居住区的停车供需现状,分析了中国城市居住区停车配建标准的现存问题及其影响因素;结合潍坊市居住小区的停车特性,对建筑物进行了更加合理、细化的分类,并把商住楼单独列为一类,对现状停车调查数据进行多元回归分析,建立了居住区停车需求率预测模型;根据停车需求率预测值,应用城市可持续发展理论,引入区位系数、区位修正系数和建筑物类别修正系数对停车需求率预测值进行修正,提出了一种基于修正系数并结合城市自身特性制定居住区停车配建标准的方法.研究结果表明:该方法可为停车需求率预测提供依据,使停车配建指标的制定过程更趋于定量化.     

基于BPR函数的路阻函数研究

为准确描述大连市道路交通阻抗,在美国BPR函数的基础上,引入影响车流通行时间的交叉口密度、道路限速、公交站点密度、饱和度等主要因素,建立了启发式道路阻抗函数.通过对大连市主干路的实证研究,利用非线性回归的方法标定了启发式路阻函数,并同美国BPR函数、重新标定BPR函数相互进行了比较.结果显示,启发式BPR函数更能准确地反映道路的车流行驶速度.     

Comparison of pedestrian trip generation models

Using Poisson regression and negative binomial regression, this paper presents an empirical comparison of four different regression models for the estimation of pedestrian demand at the regional level and finds the most appropriate model with reference to the National Household Travel Survey (NHTS) 2001 data for the Baltimore (USA) region. The results show that Poisson regression seems to be more appropriate for pedestrian trip generation modeling in terms of χ² ratio test, Pseudo R², and Akaike's information criterion (AIC). However, R² based on deviance residuals and estimated log‐likelihood value at convergence confirmed the empirical studies that negative binomial regression is more appropriate for the over‐dispersed dependent variable than Poisson regression. Copyright © 2011 John Wiley & Sons, Ltd.     

Modeling Car Ownership in Turkey Using Fuzzy Regression

Abstract

This article develops a model which can be used to determine car ownership in Turkey. Because of the lack of disaggregated data, the model is based on aggregated data. As owning a car is mainly affected by economic, social and demographic factors, the car ownership model has a multi-variable form. In order to explain the effects of these factors on car ownership in Turkey, a fuzzy multiple-regression model is used. The major reason for applying fuzzy regression is to overcome the intercorrelation problem associated with the independent variables. In this study, the urbanization rate, average family size, gross national product per capita, average car cost, gasoline price and total length of roads are selected as independent variables. The results show that, by applying a multi-variable approach to possibilistic regression, the model provides not only a crisp output but also an output range for car ownership in Turkey between 1970 and 2000.     

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对城市的道路交通运行状况进行全面分析评估并实时监控、预测,可以有效地消除交通隐患,增强城市交通管理部门对城市交通的管控能力.本文基于北京市典型道路交通流特性分析及已有的道路交通流预测模型,提出道路交通运行状态组合预测模型,确定了非参数回归模型作为预测模型的核心,组合使用傅立叶历史估算模型、非参数自回归模型和非参数邻域回归模型对北京市典型道路的交通运行状态进行预测.针对北京市道路交通流信息采集系统实际情况及未来预测信息图形化发布的需要,提出了道路交通流预测系统的异构数据融合方法及道路编码模型及方法.     

组合预测模型在铁路货运量预测中的应用

货运量预测是铁路运输规划的基础,单一预测方法很难准确有效地进行运量预测。探讨组合模型在铁路货运量预测中的应用,以全铁路货运量及社会经济发展状况为样本,对未来铁路货运量进行预测。实证预测结果表明：组合预测模型能有效综合各模型的有用信息,从而提高模型预测精度,与单一模型相比,该方法具有较好的实用价值。     

财务报告舞弊识别的实证研究

随着舞弊手段日趋隐蔽,需要建立一个快速有效的识别模型。本文选取了24个相关指标作为解释变量,选取了72家财务报告舞弊上市公司作为样本。首先建立Logistic回归模型,模型的判断率达到了71．7％。然后将Logistie回归得到的7个解释变量,用运到BP神经网络模型之中,使判则率达到87．1％,高于出了16％。说明13I）神经网络的总体识别率更高。     

Data Review of Transportation Infrastructure Public–Private Partnership: A Meta-Analysis

The limited understanding of public–private partnerships (P3s) for transportation infrastructure finance has been generally attributed to a lack of data. The more fundamental question of how P3 data are utilized in the literature is more relevant and critical, but remains unclear. This study investigates this question by examining the linkages between research objectives and data characteristics through a meta-analysis of infrastructure P3 studies using multinomial regressions. It analyzes 95 empirical studies that adopt actual data, selected from a P3 research database that includes over 345 studies and are classified into five categories including performance, contract, risk, value for money, and institutional factors. Results show that the case studies are less frequently utilized to understand P3s' institutional issues compared to those that focus on P3s' performance or VFM. Survey data are more frequently used to study P3 contracts rather than issues related to P3 project risk. We highlight the need for policy-makers to require continuing disclosure of P3 performance for validating the effectiveness of the procurement model and to improve the practice.     

Using stop bar detector information to determine turning movement proportions in shared lanes

Turning vehicle volumes at signalized intersections are critical inputs for various transportation studies such as level of service, signal timing, and traffic safety analysis. There are various types of detectors installed at signalized intersections for control and operation. These detectors have the potential of producing volume estimates. However, it is quite a challenge to use such detectors for conducting turning movement counts in shared lanes. The purpose of this paper was to provide three methods to estimate turning movement proportions in shared lanes. These methods are characterized as flow characteristics (FC), volume and queue (VQ) length, and network equilibrium (NE). FC and VQ methods are based on the geometry of an intersection and behavior of drivers. The NE method does not depend on these factors and is purely based on detector counts from the study intersection and the downstream intersection. These methods were tested using regression and genetic programming (GP). It was found that the hourly average error ranged between 4 and 27% using linear regression and 1 to 15% using GP. A general conclusion was that the proposed methods have the potential of being applied to locations where appropriate detectors are installed for obtaining the required data. Copyright © 2016 John Wiley & Sons, Ltd.