基于大数据规则挖掘的交通拥堵治理研究

随着中国城市机动车保有量的急剧增多,交通拥堵已经成为现代城市病。交通拥堵在道路网络中呈现向四周放射的传导特性,拥堵路段倾向于将拥堵扩散传导到其他相邻路段,该特性此前未被系统研究过,综合比较各种方法的适用性,从时间和大数据规则挖掘角度对拥堵建模;使用时间序列规则挖掘算法建立交通拥堵传导规律模型,并基于传导规则预测未来交通流状况;更重要的是,挖掘出来的拥堵传导规则直观可用,能够用于建立拥堵预警防治机制,完善道路路网建设规划中不合理的部分,从而达到提升交通效率的目的。研究结果证明本模型能够较好达到研究目的,挖掘出的拥堵传导规则可以精确分析交通拥堵状况并预测未来交通流状况,因此可以为交通拥堵治理决策提供重要参考。     

交通拥堵与雾霾污染的因果关系——基于收敛交叉映射技术的经验研究

交通拥堵与雾霾污染是制约现代城市发展的两大顽疾,准确识别交通拥堵与雾霾污染之间的交互影响,有助于城市管理者重新审视现行治堵与治霾政策的合理性。本文借助大数据平台采集了我国99个城市的高德拥堵延迟指数（CDI）、空气质量指数（AQI）及六种分项空气污染物浓度日报数据,首次采用收敛交叉映射（CCM）方法实证考察了交通拥堵与雾霾污染之间的因果关系。研究发现,CDI与AQI以及CDI与分项污染物组成的动态系统均呈现明显的非线性与弱耦合特征。基于CCM检验结果,大多数城市的CDI与AQI之间不存在显著的因果关系;从分项空气污染物的角度,大多数城市的CDI与主要空气污染物之间不存在显著因果关系,但与次要空气污染物之间却存在显著的单向或双向因果关系。上述结果表明,尽管交通拥堵与雾霾污染之间有一定关联,但在因果关系上现有的经验证据并不支持两者相互影响,治堵和治霾不能“一箭双雕”而必须“双管齐下”。本文的研究在经验上丰富了关于交通拥堵与雾霾污染交互影响的讨论,对城市管理者更加谨慎与合理地制定治堵政策与治霾政策有重要现实意义。     

Modelling the travel time of transit vehicles in real‐time through a GTFS‐based road network using GPS vehicle locations

Predicting the arrival time of a transit vehicle involves not only knowledge of its current position and schedule adherence, but also traffic conditions along the remainder of the route. Road networks are dynamic and can quickly change from free‐flowing to highly congested, which impacts the arrival time of transit vehicles, particularly buses which often share the road with other vehicles, so reliable predictions need to account for real‐time and future traffic conditions. The first step in this process is to construct a framework with which road state (traffic conditions) can be estimated using real‐time transit vehicle position data. Our proposed framework implements a vehicle model using a particle filter to estimate road travel times, which are used in a second model to estimate real‐time traffic conditions. Although development and testing took place in Auckland, New Zealand, we generalised each component to make the framework compatible with other public transport systems around the world. We demonstrate the real‐time feasibility and performance of our approach in real‐time, where a combination of R and C++ was used to obtain the necessary performance results. Future work will use these estimated traffic conditions in combination with historical data to obtain reliable arrival time predictions of transit vehicles.     

公交车辆在中途站点的排队论分析

公交站台停靠区的排队问题决定了公交车辆的通行能力。把公交中途站台与公交车辆模拟成一个单服务系统、公车到达率 ,两服务率 、 的负指数分布的排队M/M/1/N系统。根据排队论理论,实测计算了北京中关村海淀黄庄、人民大学站点公交车辆排队队长,站内逗留时间等参数。结论为：城市主干道关键站台改造为主、副双公交站台制式以及调整公交线路布设,优化各线路发车频率是花费成本低,畅通成效大的解决站点塞车排队的方法。     

Forecasting Multivariate Road Traffic Flows Using Bayesian Dynamic Graphical Models,Splines and Other Traffic Variables

Traffic flow data are routinely collected for many networks worldwide. These invariably large data sets can be used as part of a traffic management system, for which good traffic flow forecasting models are crucial. The linear multiregression dynamic model (LMDM) has been shown to be promising for forecasting flows, accommodating multivariate flow time series, while being a computationally simple model to use. While statistical flow forecasting models usually base their forecasts on flow data alone, data for other traffic variables are also routinely collected. This paper shows how cubic splines can be used to incorporate extra variables into the LMDM in order to enhance flow forecasts. Cubic splines are also introduced into the LMDM to parsimoniously accommodate the daily cycle exhibited by traffic flows. The proposed methodology allows the LMDM to provide more accurate forecasts when forecasting flows in a real high‐dimensional traffic data set. The resulting extended LMDM can deal with some important traffic modelling issues not usually considered in flow forecasting models. Additionally, the model can be implemented in a real‐time environment, a crucial requirement for traffic management systems designed to support decisions and actions to alleviate congestion and keep traffic flowing.     

Locally D-Optimal Design for a Logit Model in Discrete Choice Experiment

Conjoint analysis is concerned with understanding how people make choice between products or services (alternatives) or a combination of product and service (choice set), so that businesses can design new products or services that better meet customers needs. In this situation, logit model (Multinomial Logit Model) has been used to calculate the probability related to choosing an alternative in a choice set with the highest utility. Then I considered several choice sets instead of one. In this article, I have used the locally D-optimal design for the combination of the level of attributes (two attributes each with two levels) to create alternatives. The optimal combination of alternatives in choice sets which help us to have a suitable choice.     

On weak convergence of long-range-dependent traffic processes

A possible model for communication traffic is that the amount of work arriving in successive time intervals is jointly Gaussian. This model seems to fly in the face of certain obvious and characteristic features of real traffic, such as the fact that it arrives in discrete bundles and that there is often a non-zero probability of zero traffic in a time interval of significant length. Also, the Gaussian model allows the possibility of negative traffic, which is clearly unrealistic. As the number of sources of traffic increases and the quantity of traffic in communication networks increases, however, under suitable conditions, the deviation between the distribution of real traffic and the Gaussian model will become less. The appropriate concept of topology/convergence must be used or the result will be meaningless. To identify an appropriate convergence framework, the performance statistics associated with a network, namely cell loss, delay, and, in general, statistics which can be expressed in terms of the network buffers which accumulate in the network may be used as a guide. Weak convergence of probability measures has the property that when the probability measures of traffic processes converge to that of a certain traffic process, the distribution of their performance characteristics, such as buffer occupancy, also converges in the same sense to the performance of the system to which they were converging. Real traffic appears, unambiguously, to be long-range dependent. There is an interesting example where aggregation of traffic does not seem to produce convergence to the queueing behaviour expected of Gaussian traffic, at any rate the tail characteristics do not converge to those of the Gaussian result. However, in Section 4, it is shown that if the variance of one traffic stream is finite and as a proportion of the variance of the whole traffic volume tends to zero, then the traffic in networks can be expected to converge to Gaussian in the sense of weak convergence of probability measures. It is then shown that, as a consequence, the traffic in the paradoxical example does converge in this sense also. The paradox is explained by noticing that asymptotic tail behaviour may become increasingly irrelevant as traffic is aggregated. This fact should sound a warning concerning the cavalier use of tail-behaviour as an indication of performance. Long-range dependence apparently places no inhibition on convergence to Gaussian behaviour. Convergence to a Gaussian distribution of increasing aggregates of traffic is only shown to occur for discrete time models. In fact it appears that continuous time Gaussian models do not share this property and their use for modelling real traffic may be problematic.     

中国交通运输能源效率及其影响因素分析——基于三阶段DEA和GWR方法

交通运输部门能源消耗占总能耗的比重虽然不高,但是对环境造成的影响较大。交通车辆数、人口密度、交通运营线路长度、旅客和货运量等都直接影响交通能源效率。采用三阶段数据包络模型分析各地区交通运输部门的能源效率,同时考虑到相邻地区交通运输状况的相互影响,构建空间地理加权回归模型对各个地区能源消耗的影响因素进行分析。研究结果表明:各个地区交通能源效率差异与地理区位有关,但是关系不大,主要与该地区的交通运输综合密切相关;提高交通领域能源效率的主要对策是合理进行交通运输状况的分布,调配交通运输车辆和根据不同的人口密度选择交通工具。     

物流业公共交通基础设施动态趋势分析——基于中国2001—2012年省域面板数据

采用线性潜变量发展模型对中国物流业公共交通基础设施的动态发展趋势进行实证分析。研究表明:就整体而言,中国物流业公共交通基础设施初始平均水平较高,但不能为其后续发展提供足够的动力和支撑。就省域间比较而言,无论从空间地域上,还是时间维度上,均存在着显著的不均衡,且这种不均衡表现出逐年扩大的趋势。     

证券公司失败预警研究

 内容提要：一系列国内外证券公司（投资银行）的失败危机表明,及早有效地对证券公司（投资银行）的失败进行预警极为重要。本文在借鉴国内外建立企业失败预警模型的理论和经验的基础上,以我国证券公司为研究对象,将证券公司财务失败界定为证券公司破产或被证券监管部门采取风险处置措施,选取了24家财务失败证券公司和24家财务健康证券公司为样本,有针对性地选取和设计了一系列指标,对比应用了Logit方法、Probit方法和判别分析方法,最终选用Logit方法成功建立了证券公司失败预警模型。     

人口规模、“省直管县”与地方公共品供给的影响 ——来自湖北省市、县两级数据的经验证据

 本文在构建地方公共品最优供给模型基础上，运用湖北省县级和地市级面板数据就人口规模、“省直管县”对地方公共品供给的影响进行了实证检验。研究发现：基于Bordherding-Deacon常弹性拥挤函数的模型比较有效的刻画了地方公共品的供给；地市和县人口增加产生的“规模效应”大于“拥挤效应”；在县级公共服务需求的价格弹性为正，价格机制在县域公共品供给中是失灵的，而在地市级价格弹性为负，价格机制发挥着一定作用；无论地市级还是县级，公共品需求的收入弹性都大于1而富有弹性，符合“瓦格纳法则”；上级财政补助在改善地方公共服务中的作用不明显。     

Batch sequential designs for computer experiments

Computer models simulating a physical process are used in many areas of science. Due to the complex nature of these codes it is often necessary to approximate the code, which is typically done using a Gaussian process. In many situations the number of code runs available to build the Gaussian process approximation is limited. When the initial design is small or the underlying response surface is complicated this can lead to poor approximations of the code output. In order to improve the fit of the model, sequential design strategies must be employed. In this paper we introduce two simple distance based metrics that can be used to augment an initial design in a batch sequential manner. In addition we propose a sequential updating strategy to an orthogonal array based Latin hypercube sample. We show via various real and simulated examples that the distance metrics and the extension of the orthogonal array based Latin hypercubes work well in practice.     

大学综合排名竞争策略研究——基于网大（www．netbig．com）大学排行榜的实证分析

关于提升大学综舍排名的竞争策略，可以运用累积Logit模型来研究各评价指标排名对大学综合排名的影响效应，通过提高那些对综合排名影响效应较大的指标排名，能更有效地促进综合排名的提高，从而确定有效的排名竞争策略。利用网大（www．netbig．com）“中国大学排行榜”的排名数据进行实证分析，得出排名越靠前的大学通过提升“声誉”和“学术成果”名次能最有效提升综合排名。而排名越靠后的大学则通过提升“学术资源”和“物资资源”名次能最有效提升综合排名等结论。     

Analysis of a discrete-time queue with load dependent service under discrete-time Markovian arrival process

In the study of normal queueing systems, the server’s average service times are generally assumed to be constant. However, in numerous applications this assumption may not be valid. To prevent congestion in overload control telecommunication networks, the transmission rates vary depending on the number of packets waiting in the queue. As traffics in telecommunication networks are of bursty nature and correlated, we assume that arrivals follow the discrete-time Markovian arrival process. This paper analyzes a queueing model in which the server changes its service times (rates) only at the beginning of service depending on the number of customers waiting in the queue. We obtain the steady-state probabilities at various epochs and some performance measures. In addition, varieties of numerical results are discussed to display the effect of the system parameters on the performance measures.     

政府绩效评估权重设计中AHP法之改进

政府绩效评估作为政府再造的重要内容和根本性措施,强调以结果为导向,在一定程度上带来了西方发达国家行政效率的提高和政府服务能力的增强、带来了政府与公众之间关系的改善。1990年代以来,我国政府绩效评估无论在理论上还是实践上都取得了可喜的成就。但在我国政府绩效评估实践中,仍存在着一些基本的、重大的问题,有待进一步解决。本文以公共选择理论为指导,就政府绩效评估中利用AHP法确定指标权重过程存在的新问题做了分析,并提出了改进方法。     

Measures of non orthogonality in block designs

Orthogonality is an important concept in block design. Necessary and sufficient condition for a connected block design to be orthogonal is well known. However, when a design is not orthogonal, it is not clear how much it deviates from orthogonality. In this paper, an attempt has been made to first define the measures of or indices to non orthogonality in block design and then to characterize designs possessing minimum non orthogonality indices. It is shown that a Balanced Incomplete Block Design (BIBD) and a Balanced Block Design (BBD), if exist, possess this property.     

Modelling and estimating heavy-tailed non-homogeneous correlated queues: Pareto-inverse gamma HGLM with covariates

Evidence of communication traffic complexity reveals correlation in a within-queue and heterogeneity among queues. We show how a random-effect model can be used to accommodate these kinds of phenomena. We apply a Pareto distribution for arrival (service) time of individual queue for given arrival (service) rate. For modelling potential correlation in arrival (service) times within a queue and heterogeneity of the arrival (service) rates among queues, we use an inverse gamma distribution. This modelling approach is then applied to the cache access log data processed through an Internet server. We believe that our approach is potentially useful in the area of network resource management.     

Binary Dynamic Logit for Correlated Ordinal: estimation,application and simulation

We evaluate the estimation performance of the Binary Dynamic Logit model for correlated ordinal variables (BDLCO model), and compare it to GEE and Ordinal Logistic Regression performance in terms of bias and Mean Absolute Percentage Error (MAPE) via Monte Carlo simulation. Our results indicate that when the proportional-odds assumption does not hold, the proposed BDLCO method is superior to existing models in estimating correlated ordinal data. Moreover, this method is flexible in terms of modeling dependence and allows unequal slopes for each category, and can be used to estimate an apple bloom data set where the proportional-odds assumption is violated. We also provide a function in R to implement BDLCO.     

Interaction balance for symmetrical factorial designs with generalized minimum aberration

There are two different systems of contrast parameterization when analyzing the interaction effects among the factors with more than two levels, i.e., linear-quadratic system and orthogonal components system. Based on the former system and an ANOVA model, Xu and Wu (2001) introduced the generalized wordlength pattern for general factorial designs. This paper shows that the generalized wordlength pattern exactly measures the balance pattern of interaction columns of a symmetrical design ground on the orthogonal components system, and thus an alternative angle to look at the generalized minimum aberration criterion is given. This work is partially supported by NNSF of China grant No. 10231030.     

Testing Equality of Mean Vectors in Two Sample Problem with Missing Data

Finding the influence of traffic accident on the road is helpful to analyze the characteristics of traffic flow, and take reasonable and effective control measures. Here, the detrended fluctuation analysis method is applied to investigate the complexity of time series in mixed traffic flow with a blockage induced by an accident. As a parameter to depict the long-term evolutionary behavior of the time series in traffic flow, the scaling exponent is analyzed. According to the scaling exponent, it is shown that the traffic flow time series can display long-range correlation characteristics, short-range correlation characteristics, and non-power-law relation in the long-range correlation characteristics, which is strongly dependent on the entering probability of vehicle, the ratio of slow vehicle and the blockage duration time.