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1.
An acyclic k-coloring of a graph G is a proper vertex coloring of G, which uses at most k colors, such that the graph induced by the union of every two color classes is a forest. In this note, we prove that every graph with maximum degree six is acyclically 11-colorable, thus improving the main result of Yadav et al. (2009) [11].  相似文献   
2.
In this paper, we describe a hybrid tool for hardware formal verification that links the HOL (higher-order logic) theorem prover and the MDG (multiway decision graphs) model checker. Our tool supports abstract datatypes and uninterpreted function symbols available in MDG, allowing the verification of high-level specifications. The hybrid tool, HOL-MDG, is based on an embedding in HOL of the grammar of the hardware modeling language, MDG-HDL, as well as an embedding of the first-order temporal logic Lmdg used to express properties for the MDG model checker. Verification with the hybrid tool is faster and more tractable than using either tools separately. We hence obtain the advantages of both verification paradigms.  相似文献   
3.
M. Orlinski  N. Filer 《Ad hoc Networks》2013,11(5):1641-1654
Cluster detection has been widely applied to the problem of efficient data delivery in highly dynamic mobile ad hoc networks. By grouping participants who meet most often into clusters, hierarchical structures in the network are formed which can be used to efficiently transfer data between the participants. However, data delivery algorithms which rely on clusters can be inefficient in some situations. In the case of dynamic networks formed by encounters between humans, sometimes called Pocket Switched Networks (PSNs), cluster based data delivery methods may see a drop in efficiency if obsolete cluster membership persists despite changes to behavioural patterns. Our work aims to improve the relevance of clusters to particular time frames, and thus improve the performance of cluster based data delivery algorithms in PSNs. Furthermore, we will show that by detecting spatio-temporal clusters in PSNs, we can now improve on the data delivery success rates and efficiency of data delivery algorithms which do not use clustering; something which has been difficult to demonstrate in the past.  相似文献   
4.
    
This paper presents an algorithm for nodal numbering in order to obtain a small wavefront. Element clique graphs are employed as the mathematical models of finite element meshes. A priority function containing five vectors is used, which can be viewed as a generalization of Sloan's function. These vectors represent different connectivity properties of the graph models. Unlike Sloan's algorithm, which uses two fixed coefficients, here, five coefficients are employed, based on an evaluation by artificial neural networks. The networks weights are obtained using a simple genetic algorithm. Examples are included to illustrate the performance of the present hybrid method. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   
5.
    
Recently, four canonical forms have been developed and applied to the dynamics and stability analysis of symmetric frames. In this paper, hyper‐symmetric matrices and specially structured matrices are defined and efficient methods are proposed for the eigensolution of such matrices. Applications are extended to hyper‐graphs and specially structured graphs. Simple methods are developed for calculating the eigenvalues of the Laplacian matrices of such graphs. The developments presented in this paper can also be considered as generalization of Form II and Form III symmetry, previously defined by the authors. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   
6.
对于图的同构判定问题、Ramsey理论、计算Folkman数等图论的研究方向,研究人员通常需要用计算机程序生成并处理大量的简单无向图.为了节省内存和外存空间、提高程序运行速度,应该对图进行压缩存储.文中对目前研究中广泛采用的简单无向图graph6存储格式进行了介绍,并给出了将图的邻接表存储格式转换为graph6存储格式的程序片段.  相似文献   
7.
8.
    
Social networks are usually modeled and represented as deterministic graphs with a set of nodes as users and edges as connection between users of networks. Due to the uncertain and dynamic nature of user behavior and human activities in social networks, their structural and behavioral parameters are time varying parameters and for this reason using deterministic graphs for modeling and analysis of behavior of users may not be appropriate. In this paper, we propose that stochastic graphs, in which weights associated with edges are random variables, may be a better candidate as a graph model for social network analysis. Thus, we first propose generalization of some network measures for stochastic graphs and then propose six learning automata based algorithms for calculating these measures under the situation that the probability distribution functions of the edge weights of the graph are unknown. Simulations on different synthetic stochastic graphs for calculating the network measures using the proposed algorithms show that in order to obtain good estimates for the network measures, the required number of samples taken from edges of the graph is significantly lower than that of standard sampling method aims to analysis of human behavior in online social networks.  相似文献   
9.
    
Consensus strategies find extensive applications in coordination of robot groups and decision-making of agents. Since balanced graph plays an important role in the average consensus problem and many other coordination problems for directed communication networks, this work explores the conditions and algorithms for the digraph balancing problem. Based on the analysis of graph cycles, we prove that a digraph can be balanced if and only if the null space of its incidence matrix contains positive vectors. Then, based on this result and the corresponding analysis, two weight balance algorithms have been proposed, and the conditions for obtaining a unique balanced solution and a set of analytical results on weight balance problems have been introduced. Then, we point out the relationship between the weight balance problem and the features of the corresponding underlying Markov chain. Finally, two numerical examples are presented to verify the proposed algorithms.  相似文献   
10.
    
Entity linking is a fundamental task in natural language processing. The task of entity linking with knowledge graphs aims at linking mentions in text to their correct entities in a knowledge graph like DBpedia or YAGO2. Most of existing methods rely on hand‐designed features to model the contexts of mentions and entities, which are sparse and hard to calibrate. In this paper, we present a neural model that first combines co‐attention mechanism with graph convolutional network for entity linking with knowledge graphs, which extracts features of mentions and entities from their contexts automatically. Specifically, given the context of a mention and one of its candidate entities' context, we introduce the co‐attention mechanism to learn the relatedness between the mention context and the candidate entity context, and build the mention representation in consideration of such relatedness. Moreover, we propose a context‐aware graph convolutional network for entity representation, which takes both the graph structure of the candidate entity and its relatedness with the mention context into consideration. Experimental results show that our model consistently outperforms the baseline methods on five widely used datasets.  相似文献   
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