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371.
本文详细阐述了一般公路工程路基路面病害及产生病害原因,并针对路面常见病害,根据施工现场所处地质环境,结合已有经验,提出针对性解决方案。对突发性病害、预测难度大等病害,提前做出预防并提出最佳治理方案,降低病害对公路工程的破坏。  相似文献   
372.
本文采用水热法制备了一系列的二氧化锰粉末状晶体。探索了反应温度、氧化剂浓度、压力等因素对二氧化锰晶型、结晶度与形貌的影响及其内在联系。结果表明反应温度、氧化剂浓度、压力对二氧化锰晶型均有影响,氧化剂浓度对其晶型影响尤为明显。温度对形貌影响较为明显。在晶型相同情况下,二氧化锰结晶度正相关于其形貌规整度。  相似文献   
373.
随着《铁路基本建设项目投资管理办法》(铁总计统〔2017〕179号)及《关于铁路建设项目清理概算工作的通知》(发改投资电〔2019〕1号)文的出台,标志着铁路建设项目概算清理工作,将逐步交由建设单位按照不突破初步设计批复金额进行处理,因此初步设计阶段如何确保招标预算金额的准确性,体现的越来越为重要,本文通过对500米长轨营业线火车市场运费与编制办法计算运费的分析,量化两者费用存在的差异,列明差异原因,并提出相关建议。  相似文献   
374.
为了总结面向智能车辆的现役道路设施行驶适应性,即现役道路基础设施承载智能车辆行驶的适宜程度,阐述自主智能驾驶定义与驾驶自动化等级分类,在此基础上剖析不同等级间的人机功能差异,并分别从感知层、感知-决策层、决策-控制层探讨与道路设计要素相关联的人机功能差异,通过归纳总结智能车辆与道路几何要素、路面性能及其他道路要素(如道路标线)的相互作用机制研究,从道路工程角度及其他道路要素方面回顾该领域的研究现状,指出存在的问题和未来发展方向。研究结果表明:相比传统车辆,配置高等级自动驾驶系统的智能车辆对现役道路设施行驶适应性最高,主动安全系统次之,而驾驶辅助及有条件自动驾驶系统适应性不足。而目前研究主要问题包括:难以归纳、标定不同驾驶自动化等级间的人机功能差异及其对于道路设计参数的需求设计值;测试道路场景条件过于理想,考虑的驾驶自动化等级单一,试验规模和样本有限;道路几何、路面性能以及道路标志、标线等道路要素与智能车辆间的相互作用机制研究不足,缺乏与不同道路场景相匹配的智能车辆驾驶特征数据的获取手段。因此建议:重视并推动与道路设计要素相关联的关键人机功能差异指标信息共享;联合高保真且可交互的道路场景、高精度感知传感器物理模型、车辆动力学模型及微观交通流模型,利用测试场景自动化生成、极限工况场景搜寻与泛化等技术开展智能驾驶虚拟测试,突破现有研究的深度和广度;探索反映不同等级智能车辆的道路行驶适应性特征指标与评价标准,精准、有效地评估预测复杂道路场景及不利道路条件下的行驶适应性。  相似文献   
375.
为增强船内部电器柜的抗冲击性能,采用有限元法对船内不同安装型式的电器柜结构进行了模态和抗冲击性能仿真分析,通过对比分析得出了使用撑杆加固型式安装的电器柜能显著提高船内电器柜的抗冲击性能的结论,并确定了电器柜抗冲击优化设计方案。  相似文献   
376.
浙江与韩国在土地面积、 人口数量、 资源禀赋以及区位条件等多个方面都十分相似, 两者具有很强的可比性。 同时, 两者在经济发展水平以及铁路发展水平等方面也表现出了一定的差距。 文章以铁路运输为切入点, 分别回顾和总结了浙江和韩国两地的铁路发展历程和铁路运输现状。 在充分比较和分析两地铁路发展水平的基础上, 提出了韩国铁路发展对浙江的几点启示: 首先, 浙江应进一步扩大铁路网规模和密度; 其次, 浙江铁路将继续发挥对经济发展的拉动作用, 但随着时间推移拉动效应逐渐减弱; 最后, 浙江应积极探索和制定更为灵活多样的票制票价, 以吸引更多群体类型的旅客选择铁路出行。  相似文献   
377.
Computed tomography (CT) reconstruction with a well-registered priori magnetic resonance imaging (MRI) image can improve reconstruction results with low-dose CT, because well-registered CT and MRI images have similar structures. However, in clinical settings, the CT image of patients does not always match the priori MRI image because of breathing and movement of patients during CT scanning. To improve the image quality in this case, multi-group datasets expansion is proposed in this paper. In our method, multi-group CT-MRI datasets are formed by expanding CT-MRI datasets. These expanded datasets can also be used by most existing CT-MRI algorithms and improve the reconstructed image quality when the CT image of a patient is not registered with the priori MRI image. In the experiments, we evaluate the performance of the algorithm by using multi-group CT-MRI datasets in several unregistered situations. Experiments show that when the CT and priori MRI images are not registered, the reconstruction results of using multi-group dataset expansion are better than those obtained without using the expansion.  相似文献   
378.
Computer-aided hip surgery planning and implant design applications require accurate segmentation of femoral head and proximal acetabulum. An accurate outer surface extraction of femoral head using marching cubes algorithm remains challenging due to deformed shapes and extremely narrow inter-bone regions. In this paper, we present an automatic and fast approach for segmentation of femoral head and proximal acetabulum which leads to accurate and compact representation of femoral head using marching cubes algorithm. At first, valley-emphasized images are constructed from original images so that valleys stand out in high relief. Otsu’s multiple thresholding technique is applied to seperate the images into bone and non-bone classes. Region growing method and threedimensional (3D) morphological operations are performed to fill holes in the bone. In the reclassification process, the bone regions are further segmented, and the boundaries of the bone regions are further refined based on Bayes decision rule. Finally, marching cubes algorithm is applied to reconstruct a 3D model and extract the outer surface of femoral head and proximal acetabulum. Experimental results show that this method is an accurate segmentation technique for femoral head and proximal acetabulum and it can be applied as a tool in medical practice.  相似文献   
379.
Carpooling in the US has a storied history. After experiencing a peak 20% mode share in 1980, the current share of carpooling for work trips is about 10% and the majority of these carpooling trips are made by intra-household members. Casting the choice between SOV and carpool as a social dilemma in which SOV is a noncooperative choice and carpool is a cooperative one, we propose to test two hypotheses. First, the switch from SOV to carpool and the reverse choice are attributed to different factors—structural factors, or those factors altering the objective features of a decision scenario such as travel time and travel cost, play a dominant role in the switch from carpool to SOV while psychosocial factors (attitudes and beliefs) play a critical role in the switch from SOV to carpool. Second, the two choices are underlay by different behavioral mechanisms. In particular, we expect self-justification by carpool-to-SOV switchers—after they switch from carpool to SOV, they adjusted their attitudes toward carpool accordingly to match their behavior. The analysis of the first three waves of the Puget Sound Transportation Panel supports these two hypotheses. Our study results recommend developing programs and policies that aim at influencing people’s subjective assessments of carpooling, in addition to the existing ones that mostly focus on incentivizing carpooling, and differentiating between programs seeking to encourage SOV users to switch to carpool and those aiming to maintain existing carpoolers.  相似文献   
380.
[Objective ] To meet the requirements of remotely controlling ship in curved, narrow and crowded inland waterways, this paper proposes an approach that consists of CNN-based algorithms and knowledge based models under ship-shore cooperation conditions. [Method]On the basis of analyzing the characteristics of ship-shore cooperation, the proposed approach realizes autonomous perception of the environment with visual simulation at the core and navigation decision-making control based on deep reinforcement learning, and finally constructs an artificial intelligence system composed of image deep learning processing, navigation situation cognition, route steady-state control and other functions. Remote control and short-time autonomous navigation of operating ships are realized under inland waterway conditions, and remote control of container ships and ferries is carried out. [Results]The proposed approach is capable of replacing manual work by remote orders or independent decision-making, as well as realizing independent obstacle avoidance, with a consistent deviation of less than 20 meters. [Conclusions]The developed prototype system carries out the remote control operation demonstration of the above ship types in such waterways as the Changhu Canal Shenzhou line and the Yangtze River, proving that a complete set of algorithms with a CNN and reinforcement learning at the core can independently extract key navigation information, construct obstacle avoidance and control awareness, and lay the foundation for inland river intelligent navigation systems. © 2022 Journal of Clinical Hepatology. All rights reserved.  相似文献   
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