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961.
[Objective]Aiming at the problem of too many influencing factors and too little reference data for determining the dimensions of medium-sized cruise ships in the concept phase, a simplified multi-objective optimization method based on the fitting of dimensions and performance is proposed. [Method]First, the dimension relations of medium-sized cruise ships are analyzed and the influence of the latest SOLAS requirements used to determine the optimization range. Second, the influence of cruise ship dimensions on space, resistance, stability and seakeeping are analyzed. Next, based on the principles of genetic algorithms, a multiobjective optimization algorithm with high robustness and high engineering adaptability is determined to establish a multi-objective optimization model for the concept design of medium-sized cruise ships. Finally, the Pareto solution obtained by multi-objective optimization is analyzed to provide initial references for determining the dimensions of the target cruise ship. [Results]Implemented via a genetic algorithm, the optimization program proposed herein is applied in the concept design of a medium-sized cruise ship in order to optimize the initial dimensions, thereby achieving the expected outcome of providing reasonable initial dimensions for cruise ship design. [Conclusion ] The proposed simplified multi-objective optimization model can provide feasible initial dimensions for medium-sized cruise ships in the concept phase. As the Pareto solution obtained by multi-objective optimization has different focuses such as resistance and stability, the most suitable solution needs to be selected according to the design object. © 2023 Chinese Journal of Ship Research. All rights reserved. 相似文献
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为了进一步提高车辆跟车过程中的跟踪性、安全性、舒适性和燃油经济性,针对已有间距策略表现过于保守或反应过于激烈等不足之处,提出了一种预测恒定车头时距策略。该策略考虑了相对加速度,建立了一种预测型期望车间距模型,进而应用于模型预测控制的多目标自适应巡航控制系统中,能进一步提高模型预测控制对多个控制目标的综合协调能力。搭建上层控制器、下层PID控制器、油门制动切换、逆纵向动力学模型。在多工况下仿真,通过建立性能评判指标对多目标进行量化分析。结果表明,所提出的间距策略在保证安全性的前提下,提升了自适应巡航控制系统的综合性能。在不同驾驶风格的车头时距下,跟踪性、舒适性和燃油经济性均有良好表现。 相似文献
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This article introduces novel extreme value prediction method that can be used for a variety of offshore engineering applications. First, to demonstrate the novel method, fictitious data from a non-linear Duffing oscillator and measured wave heights were used as examples. The second incident included a container ship that experienced significant deck panel strains while traveling across the Atlantic Ocean in bad weather. The main concern for cargo ship transportation is potential loss of container owing to violent movements. It is challenging to model such a situation because waves and ship motions are both non-stationary and complicatedly nonlinear. Extreme motions greatly increase the role of nonlinearities, activating effects of second and higher order.Furthermore, due to the scaling and the choice of sea state, laboratory testing may also be called into doubt. Therefore, data collected from actual ships during difficult weather voyages offers a special perspective on the statistics of ship motions.This paper aims to highlight an alternative method of extrapolation that is based on intrinsic properties of the data set itself and does not assume any extrapolation functional class. Extreme value predictions typically originate from certain statistical distribution functional classes to fit the data and then extrapolate. Engineering design can make use of the unique extrapolation method that has been proposed. The proposed method's forecast accuracy has been verified in comparison to the Averaged Conditional Exceedance Rate (ACER) extrapolation method. 相似文献
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