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排序方式: 共有10000条查询结果,搜索用时 15 毫秒
991.
Uniprocessor schedulability theory made great strides, in part, due to the simplicity of composing the delay of a job from
the execution times of higher-priority jobs that preempt it. In this paper, we bound the end-to-end delay of a job in a multistage
pipeline as a function of job execution times on different stages under preemptive as well as non-preemptive scheduling. We
show that the end-to-end delay is bounded by that of a single virtual “bottleneck” stage plus a small additive component. This contribution effectively transforms the pipeline into a
single stage system. The wealth of schedulability analysis techniques derived for uniprocessors can then be applied to decide
the schedulability of the pipeline. The transformation does not require imposing artificial per-stage deadlines, but rather
models the pipeline as a whole and uses the end-to-end deadlines directly in the single-stage analysis. It also does not make
assumptions on job arrival patterns or periodicity and thus can be applied to periodic and aperiodic tasks alike. We show
through simulations that this approach outperforms previous pipeline schedulability tests except for very short pipelines
or when deadlines are sufficiently large. The reason lies in the way we account for execution overlap among stages. We discuss
how previous approaches account for overlap and point out interesting differences that lead to different performance advantages
in different cases. Further, we also show that in certain cases non-preemptive scheduling can result in higher system utilization
than preemptive scheduling in pipelined systems. We hope that the pipeline delay composition rule, derived in this paper,
may be a step towards a general schedulability analysis foundation for large distributed systems.
相似文献
Tarek AbdelzaherEmail: |
992.
Dynamic memory allocation has been used for decades. However, it has seldom been used in real-time systems since the worst
case of spatial and temporal requirements for allocation and deallocation operations is either unbounded or bounded but with
a very large bound.
In this paper, a new allocator called TLSF (Two Level Segregated Fit) is presented. TLSF is designed and implemented to accommodate
real-time constraints. The proposed allocator exhibits time-bounded behaviour, O(1), and maintains a very good execution time. This paper describes in detail the data structures and functions provided by
TLSF. We also compare TLSF with a representative set of allocators regarding their temporal cost and fragmentation.
Although the paper is mainly focused on timing analysis, a brief study and comparative analysis of fragmentation incurred
by the allocators has been also included in order to provide a global view of the behaviour of the allocators.
The temporal and spatial results showed that TLSF is also a fast allocator and produces a fragmentation close to that caused
by the best existing allocators.
相似文献
Alfons Crespo (Corresponding author)Email: |
993.
Michael Carl Maite Melero Toni Badia Vincent Vandeghinste Peter Dirix Ineke Schuurman Stella Markantonatou Sokratis Sofianopoulos Marina Vassiliou Olga Yannoutsou 《Machine Translation》2008,22(1-2):67-99
METIS-II was an EU-FET MT project running from October 2004 to September 2007, which aimed at translating free text input without resorting to parallel corpora. The idea was to use “basic” linguistic tools and representations and to link them with patterns and statistics from the monolingual target-language corpus. The METIS-II project has four partners, translating from their “home” languages Greek, Dutch, German, and Spanish into English. The paper outlines the basic ideas of the project, their implementation, the resources used, and the results obtained. It also gives examples of how METIS-II has continued beyond its lifetime and the original scope of the project. On the basis of the results and experiences obtained, we believe that the approach is promising and offers the potential for development in various directions. 相似文献
994.
This research introduces a new optimality criterion for motion planning of wheeled mobile robots based on a cost index that assesses the nearness to singularity of forward and
inverse kinematic models. Slip motions, infinite estimation error and impossible control actions are avoided escaping from singularities. In addition, high amplification of wheel velocity errors and high wheel velocity values are
also avoided by moving far from the singularity. The proposed cost index can be used directly to complement path-planning and motion-planning techniques (e.g. tree graphs, roadmaps, etc.) in order to select the optimal collision-free path or trajectory among several possible solutions. To illustrate the applications of the proposed
approach, an industrial forklift, equivalent to a tricycle-like mobile robot, is considered in a simulated environment. In particular, several results are
validated for the proposed optimality criterion, which are extensively compared to those obtained with other classical optimality criteria, such as shortest-path, time-optimal and minimum-energy. 相似文献
995.
Cheng-Jian Lin Yong-Cheng Liu Chi-Yung Lee 《Journal of Intelligent and Robotic Systems》2008,52(2):285-312
This study presents a wavelet-based neuro-fuzzy network (WNFN). The proposed WNFN model combines the traditional Takagi–Sugeno–Kang
(TSK) fuzzy model and the wavelet neural networks (WNN). This study adopts the non-orthogonal and compactly supported functions
as wavelet neural network bases. A novel supervised evolutionary learning, called WNFN-S, is proposed to tune the adjustable
parameters of the WNFN model. The proposed WNFN-S learning scheme is based on dynamic symbiotic evolution (DSE). The proposed
DSE uses the sequential-search-based dynamic evolutionary (SSDE) method. In some real-world applications, exact training data
may be expensive or even impossible to obtain. To solve this problem, the reinforcement evolutionary learning, called WNFN-R,
is proposed. Computer simulations have been conducted to illustrate the performance and applicability of the proposed WNFN-S
and WNFN-R learning algorithms. 相似文献
996.
Robert F. Hadley 《Minds and Machines》2008,18(1):1-15
It is well understood and appreciated that Gödel’s Incompleteness Theorems apply to sufficiently strong, formal deductive systems. In particular, the theorems apply to systems which are adequate for conventional number theory. Less well known is that there exist algorithms which can be applied to such a system to generate a gödel-sentence for that system. Although the generation of a sentence is not equivalent to proving its truth, the present paper argues that the existence of these algorithms, when conjoined with Gödel’s results and accepted theorems of recursion theory, does provide the basis for an apparent paradox. The difficulty arises when such an algorithm is embedded within a computer program of sufficient arithmetic power. The required computer program (an AI system) is described herein, and the paradox is derived. A solution to the paradox is proposed, which, it is argued, illuminates the truth status of axioms in formal models of programs and Turing machines. 相似文献
997.
Over the last two decades, artificial neural networks (ANN) have been applied to solve a variety of problems such as pattern
classification and function approximation. In many applications, it is desirable to extract knowledge from trained neural
networks for the users to gain a better understanding of the network’s solution. In this paper, we use a neural network rule
extraction method to extract knowledge from 2222 dividend initiation and resumption events. We find that the positive relation
between the short-term price reaction and the ratio of annualized dividend amount to stock price is primarily limited to 96
small firms with high dividend ratios. The results suggest that the degree of short-term stock price underreaction to dividend
events may not be as dramatic as previously believed. The results also show that the relations between the stock price response
and firm size is different across different types of firms. Thus, drawing the conclusions from the whole dividend event data
may leave some important information unexamined. This study shows that neural network rule extraction method can reveal more
knowledge from the data. 相似文献
998.
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
999.
Action-reward learning is a reinforcement learning method. In this machine learning approach, an agent interacts with non-deterministic
control domain. The agent selects actions at decision epochs and the control domain gives rise to rewards with which the performance
measures of the actions are updated. The objective of the agent is to select the future best actions based on the updated
performance measures. In this paper, we develop an asynchronous action-reward learning model which updates the performance
measures of actions faster than conventional action-reward learning. This learning model is suitable to apply to nonstationary
control domain where the rewards for actions vary over time. Based on the asynchronous action-reward learning, two situation
reactive inventory control models (centralized and decentralized models) are proposed for a two-stage serial supply chain
with nonstationary customer demand. A simulation based experiment was performed to evaluate the performance of the proposed
two models.
Chang Ouk Kim received his Ph.D. in industrial engineering from Purdue University in 1996 and his B.S. and M.S. degrees from Korea University,
Republic of Korea in 1988 and 1990, respectively. From 1998--2001, he was an assistant professor in the Department of Industrial
Systems Engineering at Myongji University, Republic of Korea. In 2002, he joined the Department of Information and Industrial
Engineering at Yonsei University, Republic of Korea and is now an associate professor. He has published more than 30 articles
at international journals. He is currently working on applications of artificial intelligence and adaptive control theory
in supply chain management, RFID based logistics information system design, and advanced process control in semiconductor
manufacturing.
Ick-Hyun Kwon is a postdoctoral researcher in the Department of Civil and Environmental Engineering at University of Illinois at Urbana-Champaign.
Previous to this position, Dr. Kwon was a research assistant professor in the Research Institute for Information and Communication
Technology at Korea University, Seoul, Republic of Korea. He received his B.S., M.S., and Ph.D. degrees in Industrial Engineering
from Korea University, in 1998, 2000, and 2006, respectively. His current research interests are supply chain management,
inventory control, production planning and scheduling.
Jun-Geol Baek is an assistant professor in the Department of Business Administration at Kwangwoon University, Seoul, Korea. He received
his B.S., M.S., and Ph.D. degrees in Industrial Engineering from Korea University, Seoul, Korea, in 1993, 1995, and 2001 respectively.
From March 2002 to February 2007, he was an assistant professor in the Department of Industrial Systems Engineering at Induk
Institute of Technology, Seoul, Korea. His research interests include machine learning, data mining, intelligent machine diagnosis,
and ubiquitous logistics information systems.
An erratum to this article can be found at 相似文献
1000.
Ho Woo Lee Sahng Hoon Cheon Se Won Lee Jung Woo Baek 《Discrete Event Dynamic Systems》2008,18(4):537-562
This paper studies the steady-state queue length process of the MAP/G/1 queue under the dyadic control of the D-policy and multiple server vacations. We derive the probability generating function of the queue length and the mean queue
length. We then present computational experiences and compare the MAP queue with the Poisson queue.
相似文献
Ho Woo LeeEmail: |