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61.
An application of MODIS data to snow cover monitoring in a pastoral area: A case study in Northern Xinjiang, China 总被引:3,自引:0,他引:3
Tian Gang Liang Xing Yuan Liu Wen Long Li Zheng Gang Guo Ji Zhou Ren 《Remote sensing of environment》2008,112(4):1514-1526
Snow is an important land cover on the earth's surface. It is characterized by its changing nature. Monitoring snow cover extent plays a significant role in dynamic studies and prevention of snow-caused disasters in pastoral areas. Using NASA EOS Terra/MODIS snow cover products and in situ observation data during the four snow seasons from November 1 to March 31 of year 2001 to 2005 in northern Xinjiang area, the accuracy of MODIS snow cover mapping algorithm under varied snow depth and land cover types was analyzed. The overall accuracy of MODIS daily snow cover mapping algorithm in clear sky condition is high at 98.5%; snow agreement reaches 98.2%, and ranges from 77.8% to 100% over the 4-year period for individual sites. Snow depth (SD) is one of the major factors affecting the accuracy of MODIS snow cover maps. MODIS does not identify any snow for SD less than 0.5 cm. The overall accuracy increases with snow depth if SD is equal to or greater than 3 cm, and decreases for SD below 3 cm. Land cover has an important influence in the accuracy of MODIS snow cover maps. The use of MOD10A1 snow cover products is severely affected by cloud cover. The 8-day composite products of MOD10A2 can effectively minimize the effect of cloud cover in most cases. Cloud cover in excess of 10% occurs on 99% of the MOD10A1 products and 14.7% of the MOD10A2 products analyzed during the four snow seasons. User-defined multiple day composite images based on MOD10A1, with flexibilities of selecting composite period, starting and ending date and composite sequence of MOD10A1 products, have an advantage in effectively monitoring snow cover extent for regional snow-caused disasters in pastoral areas. 相似文献
62.
自主水下航行器的变质心跟踪控制 总被引:5,自引:0,他引:5
The trajectory-tracking control problem is investigated for an autonomous underwater vehicle (AUV) moving in the vertical plane using an internal point mass and a rear thruster as actuators. Combined with the dynamics of the point mass, the AUV is modeled as an underactuated system. A Lyapunov-based tracking controller is proposed by using backstepping approach to stabilize the error dynamics and force the position errors to a small neighborhood of the origin. Simulation results validate the proposed tracking approach. 相似文献
63.
Kobus Barnard Quanfu Fan Ranjini Swaminathan Anthony Hoogs Roderic Collins Pascale Rondot John Kaufhold 《International Journal of Computer Vision》2008,77(1-3):199-217
We present a new data set of 1014 images with manual segmentations and semantic labels for each segment, together with a methodology
for using this kind of data for recognition evaluation. The images and segmentations are from the UCB segmentation benchmark
database (Martin et al., in International conference on computer vision, vol. II, pp. 416–421, 2001). The database is extended by manually labeling each segment with its most specific semantic concept in WordNet (Miller et al.,
in Int. J. Lexicogr. 3(4):235–244, 1990). The evaluation methodology establishes protocols for mapping algorithm specific localization (e.g., segmentations) to our
data, handling synonyms, scoring matches at different levels of specificity, dealing with vocabularies with sense ambiguity
(the usual case), and handling ground truth regions with multiple labels. Given these protocols, we develop two evaluation
approaches. The first measures the range of semantics that an algorithm can recognize, and the second measures the frequency
that an algorithm recognizes semantics correctly. The data, the image labeling tool, and programs implementing our evaluation
strategy are all available on-line (kobus.ca//research/data/IJCV_2007).
We apply this infrastructure to evaluate four algorithms which learn to label image regions from weakly labeled data. The
algorithms tested include two variants of multiple instance learning (MIL), and two generative multi-modal mixture models.
These experiments are on a significantly larger scale than previously reported, especially in the case of MIL methods. More
specifically, we used training data sets up to 37,000 images and training vocabularies of up to 650 words.
We found that one of the mixture models performed best on image annotation and the frequency correct measure, and that variants
of MIL gave the best semantic range performance. We were able to substantively improve the performance of MIL methods on the
other tasks (image annotation and frequency correct region labeling) by providing an appropriate prior. 相似文献
64.
Behaviour based on decision matrices for a coordination between agents in a urban traffic simulation
René Mandiau Alexis Champion Jean-Michel Auberlet Stéphane Espié Christophe Kolski 《Applied Intelligence》2008,28(2):121-138
This paper describes a multi-agent coordination mechanism applied to intersection simulation situations. In a goal of urban
traffic simulation, we must consider the dynamic interactions between autonomous vehicles. The field of multi-agent systems
provides us some studies for such systems, in particular on the coordination mechanisms. Conflicts between vehicles (i.e.
agents) are very frequent in such applications, and they may cause deadlocks, particularly at intersections such as crossroads.
Our approach is based on the solving of two player games/decision matrices which characterize three basic situations. An aggregation
method generalizes to n-player games for complex crossroads. The objective of this approach consists in searching basic two-player
matrices for solving n-agent problems. To explain the principle, we describe our approach for a particular case of crossroad
with three agents. Finally, the obtained results have been examined via a tool of road traffic simulation, ARCHISIM. We assume
also that the global traffic replicates the behavior of agents in different situations. 相似文献
65.
So far, most of the applications of robotic technology to education have mainly focused on supporting the teaching of subjects
that are closely related to the Robotics field, such as robot programming, robot construction, or mechatronics. Moreover,
most of the applications have used the robot as an end or a passive tool of the learning activity, where the robot has been
constructed or programmed. In this paper, we present a novel application of robotic technologies to education, where we use
the real world situatedness of a robot to teach non-robotic related subjects, such as math and physics. Furthermore, we also
provide the robot with a suitable degree of autonomy to actively guide and mediate in the development of the educational activity.
We present our approach as an educational framework based on a collaborative and constructivist learning environment, where
the robot is able to act as an interaction mediator capable of managing the interactions occurring among the working students.
We illustrate the use of this framework by a 4-step methodology that is used to implement two educational activities. These
activities were tested at local schools with encouraging results. Accordingly, the main contributions of this work are: i) A
novel use of a mobile robot to illustrate and teach relevant concepts and properties of the real world; ii) A novel use of
robots as mediators that autonomously guide an educational activity using a collaborative and constructivist learning approach;
iii) The implementation and testing of these ideas in a real scenario, working with students at local schools.
相似文献
Alvaro Soto (Corresponding author)Email: |
66.
A dynamic workflow framework for mass customization using web service and autonomous agent techniques 总被引:3,自引:1,他引:2
Daniel J. Karpowitz Jordan J. Cox Jeffrey C. Humpherys Sean C. Warnick 《Journal of Intelligent Manufacturing》2008,19(5):537-552
Custom software development and maintenance is one of the key expenses associated with developing automated systems for mass
customization. This paper presents a method for reducing the risk associated with this expense by developing a flexible environment
for determining and executing dynamic workflow paths. Strategies for developing an autonomous agent-based framework and for
identifying and creating web services for specific process tasks are presented. The proposed methods are outlined in two different
case studies to illustrate the approach for both a generic process with complex workflow paths and a more specific sequential
engineering process. 相似文献
67.
研究了无线传感器网络中基于距离的决策融合算法,并针对它们的不足,提出了一种基于区域决策的距离均值融合算法.该算法首先采用目标定位运算估计目标源的位置,并划定以目标源为中心的一定区域为有效区域,然后根据距离均值模型计算有效区域内传感节点的可信度权重,并将其决策和相应的权重上传到融合中心进行决策融合.仿真实验表明,该算法比其它基于距离的融合算法具有更高的检测概率和较好的抗噪性能,适合中大规模无线传感器网络. 相似文献
68.
针对新疆民间艺术图案纹理复杂,相似程度高,提取不同特征会使分类器产生不同错误率的问题,提出了优化组合特征技术,建立了组合特征选择的评价模型.该模型的建立先是利用7种不同算法提取纹理描述特征.针对特征过多或欠佳而造成分类精度不高或分类实时性差的缺点,引入特征选取模型对特征进行可靠性、可区别性及独立性的标定及测评.给出最佳组合特征的参考模型及评价模式,提取较优特征组合,从而解决了特征过多或欠佳的问题.通过新疆民间艺术织物图案识别为例,实例结果证实了该评价方法的实用性. 相似文献
69.
70.