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由于传统的系统可靠性建模与分析方法在描述时间、过程变量和操纵员等的动态影响时存在困难,而无法满足复杂动态系统可靠性分析的需要。对具有动态随机性故障的可修系统采用静态近似处理,经常会导致计算的可靠性指标与实际情况相差较大。针对动态分析问题,应用马尔科夫过程理论建立了系统中部件可靠性参数随时间变化的状态转移方程,根据冷却水系统的原理和运行特点建立了冷却水系统的数学计算模型,并运用算例对该方法进行了分析。分析结果表明,该模型可以合理地分析计算冷却水系统的不可用度随时间的变化。 相似文献
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Standard economic policy evaluation allows the realization of projects if the aggregated economic benefit outweighs their
costs. The use of one single aggregated welfare measure for evaluating and ranking projects has often been criticized for
many reasons. A major issue is that differentiated effects on individuals or subgroups of the population are not taken into
consideration. This leads to the need for transport planning tools that provide additional information for politicians and
decision makers. The microscopic multi-agent simulation approach presented in this paper is capable of helping to design better
solutions in such situations. In particular, it is shown that the inclusion of individual income in utility calculations allows
a better understanding of problems linked to public acceptance. First, individual income-contingent utility functions are
estimated based on survey data in order to describe human mobility behavior. Subsequently, using the MATSim framework, the
implementation is tested in a test scenario. Furthermore, and going beyond Franklin (2006), it is shown that the approach works in a large-scale real world example. Based on a hypothetical speed increase of public
transit, effects on the welfare distribution of the population are discussed. It is shown that the identification of winners
and losers seems to be quite robust. However, results indicate that a conversion or aggregation of individual utility changes
for welfare analysis is highly dependent on the functional form of the utility functions as well as on the choice of the aggregation
procedure. 相似文献
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Khandker M. Nurul Habib 《Transportation》2011,38(1):123-151
The paper presents a modeling framework for dynamic activity scheduling. The modeling framework considers random utility maximization
(RUM) assumption for its components in order to capture the joint activity type, location and continuous time expenditure
choice tradeoffs over the course of the day. The dynamics of activity scheduling process are modeled by considering the history
of activity participation as well as changes in time budget availability over the day. For empirical application, the model
is estimated for weekend activity scheduling using a dataset (CHASE) collected in Toronto in 2002–2003. The data set classifies
activities into nine general categories. For the empirical model of a 24-h weekend activity scheduling, only activity type
and time expenditure choices are considered. The estimated empirical model captures many behavioral details and gives a high
degree of fit to the observed weekend scheduling patterns. Some examples of such behavioral details are the effects of time
of the day on activity type choice for scheduling and on the corresponding time expenditure; the effects of travel time requirements
on activity type choice for scheduling and on the corresponding time expenditure, etc. Among many other findings, the empirical
model reveals that on the weekend the utility of scheduling Recreational activities for later in the day and over a longer
duration of time is high. It also reveals that on the weekend, Social activity scheduling is not affected by travel time requirements,
but longer travel time requirements typically lead to longer-duration social activities. 相似文献
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A recent survey reported that many commuter-cyclists had enjoyed leisure bicycling on a regular basis prior to becoming a
commuter-cyclist. While bicycling for leisure, it is assumed that they considered various factors that led them to consider
becoming commuter-cyclists. This study began with the question of how long it would take for a leisure-cyclist to become a
commuter-cyclist, and it focused on the time that elapsed between leisure-cyclists transitioning to commuter-cycling. In order
to analyze the time frame, it was hypothesized that the probability that a leisure-cyclist would become a commuter-cyclist
at a certain time would be conditional on the duration that elapsed from the onset of leisure cycling till that time, which
represents the “snowballing” or “inertial” dynamics of duration. A robust methodology, which is known as the “hazard model,”
was adopted to accommodate such characteristics of a time period. In addition, various external covariates such as individual-specific
characteristics, variables associated with the current or previous commuting mode, supply variables regarding bicycle facilities,
and individual latent propensities were adopted to account for the duration of changes that would be generally applicable.
As a result, many useful results were derived that could be used in fomenting policies to promote cycling to work. It was
found that government should invest in establishing segregated lanes for leisure- and commuter-cyclists. It also turned out
that a long distance to work hinders a leisure-cyclist from progressing to commuter-cycling. According to the results, young
white-collar workers who live in high-rise apartments and enjoy intensive leisure-cycling in groups, are a good target toward
whom promotions for commuter-cycling should be focused. However, an unfortunate development was that, when compared with car-commuters,
it was found that transit-commuters are more likely to become commuter-cyclists. 相似文献
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