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建立了一个新的二元copula类,并证明了它所包含的二元函数是正二次相依的;同时给出了新的copula类的应用和相依性的讨论.  相似文献   
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Day-to-day variation in the travel times of congested urban transportation networks is a frustrating phenomenon to the users of these networks. These users look pessimistically at the path travel times, and learn to spend additional time to safeguard against serious penalties that await late arrivals at the destinations. These additional expenses are charges similar to the tolls in system equilibrium flow problem, but may not be collected. With this conjecture, the user equilibrium (UE) formulation of congested network flow problem would lack some necessary factors in addressing appropriate path choices. This study, following a previous work proposing pessimistic UE (PUE) flow, aims to show how to measure this additional travel cost for a link, and investigates how different is PUE from UE, and when such differences are pronounced. Data are collected from the peak-hour travel times for the links of paths in the city of Tehran, to estimate the variance of travel times for typical links. Deterministic functions are obtained by calibrating the standard deviation of the daily variations of link travel times, and probabilistic functions by the technique of copula. UE and PUE traffic assignment models are built and applied to three large cities of Mashhad, Shiraz, and Tehran in Iran. The results show that the estimated flows by PUE model replicate the observed flows in screen lines much better than the UE model, particularly for longer trips. Since PUE is computationally equivalent to UE, this improvement is attained virtually at no cost.  相似文献   
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为评价各突发事件相互关联时的原油海运网络中关键节点的连通可靠性,引入vine copula构建各突发事件的联合分布,并基于各突发事件的联合分布和条件分布进行节点连通可靠性评估.以马六甲海峡为例进行案例分析,结果表明:节点隶属国家政局不稳定及军事冲突与海盗及海上恐怖主义间具有对称的尾部相关性,而海盗及海上恐怖主义和船舶交通事故分别与恶劣天气具有下尾相关性.此外,在节点隶属国家政局不稳定及军事冲突、恶劣天气和海盗及海上恐怖主义的作用下,马六甲海峡的连通可靠性较低,仅为0.239 5;而在节点隶属国家政局不稳定及军事冲突、恶劣天气和船舶交通事故的作用下,马六甲海峡的连通可靠性相对较高.  相似文献   
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Cycling is attracting renewed attention as a mode of transport in western urban environments, yet the determinants of usage are poorly understood. In this paper we investigate some of these using intraday bicycle volumes collected via induction loops located at ten bike paths in the city of Melbourne, Australia, between December 2005 and June 2008. The data are hourly counts at each location, with temporal and spatial disaggregation allowing for the impact of meteorology to be measured accurately for the first time. Moreover, during this period petrol prices varied dramatically and the data also provide a unique opportunity to assess the cross-price elasticity of demand for cycling. Over-dispersed Poisson regression models are used to model volumes at each location and at each hour of the day. Seasonality and the impact of weather conditions are modelled as semiparametric and estimated using recently developed multivariate penalized spline methodology. Unlike previous studies that use aggregate data, the empirical results show a substantial meteorological and seasonal component to usage. They also suggest there was substitution into cycling as a mode of transport in response to increases in petrol prices, particularly during peak commuting periods and by commuters originating in wealthy and inner city neighbourhoods. Last, we extend the approach to a multivariate longitudinal count data model using a Gaussian copula estimated by Bayesian data augmentation. We find first order serial dependence in the hourly volumes and a ‘return trip’ effect in daily bicycle commutes.  相似文献   
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