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671.
672.
This paper proposes a new activity-based transit assignment model for investigating the scheduling (or timetabling) problem
of transit services in multi-modal transit networks. The proposed model can be used to generate the short-term and long-term
timetables of multimodal transit lines for transit operations and service planning purposes. The interaction between transit
timetables and passenger activity-travel scheduling behaviors is captured by the proposed model, as the activity and travel
choices of transit passengers are considered explicitly in terms of departure time choice, activity/trip chain choices, activity
duration choice, transit line and mode choices. A heuristic solution algorithm which combines the Hooke–Jeeves method and
an iterative supply–demand equilibrium approach is developed to solve the proposed model. Two numerical examples are presented
to illustrate the differences between the activity-based approach and the traditional trip-based method, together with comparison
on the effects of optimal timetables with even and uneven headways. It is shown that the passenger travel scheduling pattern
derived from the activity-based approach is significantly different from that obtained by the trip-based method, and that
a demand-sensitive (with uneven headway) timetable is more efficient than an even-headway timetable. 相似文献
673.
In this paper we review freight forecasting models and current advances and needs with respect to data and model development.
We then present a case study to suggest which models should be developed for the State of California in the US. We suggest
several alternatives including an aggregate commodity flow model, a disaggregate regional logistics model and a hybrid regional
logistics model with a truck touring model. We point out however, that the data requirements for the latter model would be
extensive. In addition, the development of hybrid models, for example progress in the integration of regional logistics models
with urban truck touring models, will introduce new problems such as reconciling the outputs of multiple models for consistency. 相似文献
674.
A new model system dealing with trips of length up to 100 km has recently been developed in Norway. A new way of dealing with
seasonal passes for public transport is used in the travel-to-work model. The objective was to account for the fact that a
respondent that posses a seasonal pass for public transport may behave as if public transport is free on the day they report
a travel diary. On the other hand, we can not assume that public transport is free for respondents that used other modes of
transport or that public transport is free to alternative destinations. This problem was solved by defining seasonal pass
as a separate alternative in the form of a nest that included all modes of travel. The cost of a seasonal pass is a common
cost for all modes in the nest and will thus not affect the choice within the nest. The estimation of this specification is
compared with the more common approach of assigning an average cost per day based on the cost of a monthly pass and the number
of workdays in a month. The comparison indicates that the “average cost per day” approach may produce biased estimates for
several parameters. It also turns out that the cost parameter for seasonal pass is higher than the parameter for “out of pocket”
cost, probably reflecting that there will be some uncertainty with respect to the actual use of a seasonal pass. 相似文献
675.
676.
The paper reports a modelling system to simulate goods movements at an urban scale. It allows joint analysis of choices made
by end-consumers (assumed to be families) and retailers. These movements are examined at two levels: analysis of commodity
flows, in terms of quantity, generated by the consumption of commodities; analysis of commodity flows, in terms of vehicles,
due to restocking. The first level allows us to calculate the goods quantity flows due to consumption and restocking; the
second level allows us to determine the service, vehicles used and target time, as well as the route chosen for restocking
sales outlets in order to estimate vehicle flows on the urban/metropolitan transportation network. The modelling system is
a multi-step model and considers a disaggregated approach for each decisional level. 相似文献
677.
Nazneen Ferdous Abdul Rawoof Pinjari Chandra R. Bhat Ram M. Pendyala 《Transportation》2010,37(3):363-390
This paper proposes a multiple discrete continuous nested extreme value (MDCNEV) model to analyze household expenditures for
transportation-related items in relation to a host of other consumption categories. The model system presented in this paper
is capable of providing a comprehensive assessment of how household consumption patterns (including savings) would be impacted
by increases in fuel prices or any other household expense. The MDCNEV model presented in this paper is estimated on disaggregate
consumption data from the 2002 Consumer Expenditure Survey data of the United States. Model estimation results show that a
host of household and personal socio-economic, demographic, and location variables affect the proportion of monetary resources
that households allocate to various consumption categories. Sensitivity analysis conducted using the model demonstrates the
applicability of the model for quantifying consumption adjustment patterns in response to rising fuel prices. It is found
that households adjust their food consumption, vehicular purchases, and savings rates in the short run. In the long term,
adjustments are also made to housing choices (expenses), calling for the need to ensure that fuel price effects are adequately
reflected in integrated microsimulation models of land use and travel. 相似文献
678.
Smart card systems have become the predominant method of collecting public transport fares in Japan. Transaction data obtained
through smart cards have resulted in a large amount of archived information on how passengers use public transportation. The
data have the potential to be used for modeling passenger behavior and demand for public transportation. This study focused
on train choices made by railway passengers. If each passenger’s train choice can be identified over a long period of time,
this information would be useful for improving the customer relationship management of the railway company and for improving
train timetables. The aim of this study was to develop a methodology for estimating which train is boarded by each smart card
holder. This paper presents a methodology and an algorithm for estimation using long-term transaction data. To validate the
computation time and accuracy of the estimation, an empirical analysis is carried out using actual transaction data provided
by a railway company in Japan. The results show that the proposed method is capable of estimating passenger usage patterns
from smart card transaction data collected over a long time period. 相似文献
679.
Philip J. Zwart Philippe G. Godin Justin Penrose Shin Hyung Rhee 《Journal of Marine Science and Technology》2008,13(4):346-355
An accurate, efficient algorithm for solving free surface flows around ship hulls is described. Accuracy is achieved using
a compressive advection discretization which maintains a sharp free surface interface representation without relying on a
small time step. Efficiency is obtained using a solution algorithm which implicitly couples velocity, pressure, and volume
fractions. The algorithm has been implemented in a computational fluid dynamics code called CFX and is validated by means
of a comparisonwith experimental data of benchmark cases in both steady and transient conditions. 相似文献
680.
In this paper, we propose the theory of Rational Beliefs as the model of expectations that extends the theory of rational expectations to the postulated environments. Under the rational beliefs paradigm, drivers do not have structural knowledge of traffic conditions and they choose their routes based only on personal experiences and decision‐making rules. We found that if drivers have different decision‐making rules and experiences, then they form different beliefs of traffic conditions (e.g. average travel time) even though they have the same public information and use the same routes. Under the rational beliefs model, drivers are not motivated to renew their beliefs because the beliefs are compatible with their experiences. Therefore, the heterogeneity of beliefs does not disappear even though they have long‐term learning. In order to investigate how drivers form their beliefs of traffic conditions under bounded information environments, numerical experiment is carried out. 相似文献