首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   2603篇
  免费   116篇
公路运输   793篇
综合类   684篇
水路运输   663篇
铁路运输   492篇
综合运输   87篇
  2024年   20篇
  2023年   19篇
  2022年   75篇
  2021年   125篇
  2020年   96篇
  2019年   40篇
  2018年   33篇
  2017年   38篇
  2016年   47篇
  2015年   92篇
  2014年   107篇
  2013年   146篇
  2012年   199篇
  2011年   203篇
  2010年   181篇
  2009年   185篇
  2008年   191篇
  2007年   242篇
  2006年   219篇
  2005年   139篇
  2004年   44篇
  2003年   49篇
  2002年   44篇
  2001年   53篇
  2000年   40篇
  1999年   19篇
  1998年   12篇
  1997年   11篇
  1996年   15篇
  1995年   10篇
  1994年   6篇
  1993年   2篇
  1992年   7篇
  1991年   3篇
  1990年   2篇
  1989年   2篇
  1988年   1篇
  1987年   1篇
  1985年   1篇
排序方式: 共有2719条查询结果,搜索用时 0 毫秒
881.
Handheld global positioning system (GPS) devices can serve as a new tool to collect an individual's trip information with advantages of low cost, accurate data, and intensive spatial coverage. Various machine learning algorithms have been explored to detected trip train information in previous studies; however, few of them focused on the evaluation and comparison of the performance and applicability of different models. Meanwhile, according to previous studies, car and bus mode detection is a thorny issue due to their similar travel characteristics, and algorithms still need to be well explored and improved to solve this problem. In this article, an innovative method is proposed to detect trip information, including trip modes, mode-changing time and location, and other attributes, from personal trajectory data. The method is a two-step process. A machine learning algorith-based module (including artificial neural network, support vector machine, random forests, and Bayesian network) is firstly used to identify walk, bicycle, and motorized trip modes (bus or car); we thoroughly compared the performance of these four algorithms. Then a second module, using critical points on the GPS trajectories, is further developed to distinguish car and bus mode, incorporated with GIS map information. Field test results show that the proposed machine learning models can all be applied for walk, bicycle, and motorized mode detection with high detection rates exceeding 90%; however, the algorithms work relatively poorly for bus and car mode detection, with results mostly below 75%. The proposed two-step method can greatly improve bus and car mode detection accuracy by 14–30%. As a result, the average mode detection rates for all the four modes are above 90%. Compared with mode detection results by using only the machine learning algorithm, the proposed two-step method has much better performance in both accuracy and consistency.  相似文献   
882.
在当前金属带式无级变速器常用的夹紧力控制方法基础上,通过台架试验标定出了临界夹紧力,并考虑温度对夹紧力的影响而引入温度修正系数;利用模糊算法选定各种不同工况下的安全系数,从而确定金属带的目标夹紧力.实车试验结果表明,应用上述方法确定的目标夹紧力,可在保证金属带不打滑的情况下,有效降低目标夹紧力,提高了金属带式无级变速器的传动效率.  相似文献   
883.
本文中首次采用与测试数据耦合的方法获取虚拟试验台架的驱动文件,作为准确的路面激励输入,以提高疲劳仿真精度.在某车型耐久性能优化中,运用该技术提高了零件的疲劳寿命.仿真与耐久性试验结果的对比表明,该方法计算精度高且资源消耗少,能有效指导汽车结构设计.  相似文献   
884.
刘成  李一兵  李宝良  马瑾 《汽车工程》2006,28(1):68-72,77
通过分析车轮与车身相互刮擦时所产生的刮擦痕迹,提出了在刮擦点的位置参数不能获得时,单纯依据刮擦痕迹包含的信息估计交通事故中肇事车辆速度的方法。  相似文献   
885.
系统地分析了冷锻件破裂的原因,提出了提高冷锻件质量的方案,研究了不同热处理状态下镦粗的极限应变。考虑到静水压应力分量具有抑制材料韧性破坏的重要特性,从能量观点出发提出了冷锻材料破裂准则。试验验证结果表明,该准则可用于金属冷锻成型的破裂预测,并可指导冷锻成型工艺的编制及模具的调试。  相似文献   
886.
887.
傅氏变换在频域能对信号整体作频谱分析,很难直接分析交流计数信号。近年来兴起的子波变换可对信号进行多尺度分析,容易提取信号特征。本文是用子波变换方法分析铁路交流计数信号。并且通过采用不同的小波基对铁路交流计数信号进行仿真,通过分析比较找到合适的小波基,结合频谱分析的方法得到铁路交流计数信号的有关参数。最后给出仿真的例子。  相似文献   
888.
Abstract

Researchers have collected extensive vehicle activity data in Beijing using GPS and attempted to develop a comprehensive database of facility- and speed-specific operating mode (OpMode) distributions of various vehicle types for estimating on-road vehicle emissions. This study developed the specific OpMode distributions of light duty vehicles (LDVs) for both restricted access and unrestricted access road types at various average speeds for characteristic analysis. (1) Strong patterns are found in the variations in OpMode distributions with the increase in the average speed: the time fraction of Decelerating/Braking remains less than 7%. The fraction of Idling decreases dramatically from 95% to 0%, while the fraction of Cruising/Accelerating increases from 2% to 94%. The fraction of Coasting increases to 28% and then decreases. (2) The time fractions for restricted access and unrestricted access are significantly different at the same average speeds, especially in Operating Modes #0, #1, #11, #12, #13, #14, #21, and #22, possibly causing an error of 20% in the emissions estimations. (3) Taxis show different OpMode distributions than those for private cars in the operating modes of Decelerating/Braking, Idling, and high-VSP modes, especially at low average speeds. The differences are derived from the more skillful driving behaviors of taxi drivers and may cause an estimation error of over 10%. Thus, the activities of taxis and private cars should be modeled separately for on-road emissions estimations.  相似文献   
889.
890.
从车联网(V2X)的不同应用角度,讨论在不同应用场景下的移动边缘计算(MEC)组网方式,为车联网(V2X)的业务实现提供技术支持。  相似文献   
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号