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1.
刘建林 《上海交通大学学报(英文版)》2005,10(3):314-317
The definitions of generalized pseudoconvex,generalized quasiconvex and its strictly generalized convexity were presented for the static programming at locally star-shaped set using the concept of right-upper derivative and the concept of sublinear. The sufficient and necessary conditions of the static programming were derived in terms of a generalized Lemmain this paper. The results obtained are useful for the further study on the duality of static programming and cover many already known conditions. 相似文献
2.
In mode choice decision, travelers consider not only travel time but also reliability of its modes. In this paper, reliability was expressed in terms of standard deviation and maximum delay that were measured based on triangular distribution. In order to estimate value of time and value of reliability, the Multinomial and Nested Logit models were used. The analysis results revealed that reliability is an important factor affecting mode choice decisions. Elasticity is used to estimate the impacts of the different policies and system improvements for water transportation mode. Among these policies, decision maker can assess and select the best alternative by doing the benefit and cost analysis based on a new market share, the value of time, and the value of reliability. Finally, a set of promising policies and system improvement of the water transportation were proposed. 相似文献
3.
基于多项Logit模型的轨道交通站点步行接驳范围 总被引:1,自引:0,他引:1
在分析步行环境、出行时间、出行费用等出行特征影响因素的基础上,运用多项Logit模型建立了居民出行方式选择模型,根据效用相当原则确定城市轨道交通步行接驳范围。根据某城市的某个轨道交通站点的调查数据,利用本文提出的方法计算该站点的步行接驳范围,与传统的接驳范围经验取值及意向调查结果进行比较,发现计算结果与调查统计结果较为一致。计算结果表明,该计算方法是有效合理的,能够为城市轨道交通站点的规划、选址和评价提供依据。 相似文献
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为了分析城市新建地铁项目对居民公共交通出行的影响,改善公交服务水平,提高公共交
通的分担率,针对大连市新建地铁线路展开研究。以大连市地铁1 号线沿线站点作为研究区域,
采用SP (Stated Preference) 调查方法,收集了300 名地铁沿线居民对常规公交以及新建地铁两种
出行方式的选择数据。通过建立二项Logit 模型,分析出行成本、换乘时间等选择方案特性变
量,出行特性变量以及出行者特性变量对于居民出行方式选择行为的影响,并计算弹性值及模型
精度。结果表明,通过调整出行成本及换乘时间可有效提高地铁分担率。由此提出相关政策建
议:对于出行成本,可从出行者年龄及出行次数两方面制定不同的优惠政策;对于换乘时间,可
从提高可达性、完善购票系统以及调整发班频率三方面进行改善。 相似文献
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This paper investigates crowding effect on the path choice of metro passengers. We show people reroute not only to avoid the delay from crowding but also to evade crowding itself. More specifically, a logit model fits best when it uses the transit delay from crowding as well as the passenger load of a connection in addition to the conventional explanatory variables. Also, we demonstrate that crowding decreases the overall welfare of metro passengers. The model is tested on the real path choice data acquired by the recent algorithm by Hong et al. (2015) known to detect the real path choice from Smart Card data in more than 90% of the cases. 相似文献
8.
为刻画托运人对港口、运输方式及陆港的联合选择行为,将港口费用、等待时间、班轮频率、货物价值、单次运量、运输成本、运输及通关时间、准班率、陆港服务作为效用变量,构建港口选择位于上层、运输方式及陆港选择位于下层的巢式Logit模型.基于辽宁部分城市集装箱托运人的RP/SP调查数据,对模型参数进行估计和检验.结果表明,低运量倾向选择公路运输,托运人对多式联运的运输成本、运输及通关时间比公路运输的更重视,对公路运输的准班率比多式联运的更重视,陆港服务对多式联运具有显著正向影响,巢式Logit模型比MNL模型具有更优的统计学特征. 相似文献
9.
ABSTRACTIn this article, we propose a new model called subjective-utility travel time budget (SU-TTB) model to capture travelers' risk-averse route choices. In the travel time budget (TTB) and mean-excess travel time (METT) model, a predefined confidence level is needed to capture the risk-aversion in route choice. Due to the day-to-day route travel time variations, the exact confidence level is hard to be predicted. With the SU-TTB model, we assume travelers' confidence level belongs to an interval that they may comply with in the route choice. The two main components of SU-TTB are the utility function and the TTB model. We can show that the SU-TTB can be reduced to the TTB and METT model with proper utility function for the confidence levels. We can also prove its equivalence with our recently proposed nonlinear-expectation route travel time (NERTT) model in some cases and give some new interpretation on the NERTT with this equivalence. Finally, we formulate the SU-TTB model as a variational inequality (VI) problem to model the risk-averse user equilibrium (RAUE), termed as generalized RAUE (GRAUE). The GRAUE is solved via a heuristic gradient projection algorithm, and the model and solution algorithm are demonstrated with the Braess's traffic network and the Nguyen and Dupuis's traffic network. 相似文献
10.