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31.
模糊C-均值(FCM)聚类算法的实现 总被引:11,自引:0,他引:11
传统的FCM算法能够将靠近边界的具有固有形状的两个簇合并成为一个大的簇.然而,对于一些稍微复杂的数据,如果没有其它的像去除小簇之类的机制的话,FCM算法很难将非常接近的类聚类到一起.给出的聚类算法是在传统FCM算法的循环之后添加了去除掉空簇的步骤,解决了上述很难将非常接近的类聚到一个簇中的问题.另外,为便于选出最优结果,在递归之后又添加了计算聚类有效性的步骤.最后用Java实现了该算法并在数据集上进行了实验,证实了改进方法的有效性. 相似文献
32.
刘敏娴 《数字社区&智能家居》2009,(11)
聚类分析是数据挖掘中的非常重要的技术,通过对数据挖掘中常用聚类算法的分类分析比较,使得人们在实际应用中能方便、快捷地找到最好的聚类算法以解决实际问题,然后通过一个实例运用聚类来进行分析和实践。 相似文献
33.
在LEACH中引入了Gur Game算法,来实现对无线传感网络中工作节点总数的控制。在节点密度较高的网络中,当算法满足它的节点密度要求时,允许部分节点进入低能耗状态同时也减少了簇头节点个数。仿真实验证明改进算法与LEACH相比能有效延长了系统的生存时间。 相似文献
34.
针对知识在非正式团体中的传播特征,结合复杂网络理论,为了企业知识不断创新,提出了一种非正式团体知识交互网络模型.通过仿真得出,在小世界网络模型下知识的传播速度和平均知识水平比其他网络模型有明显优势,进而在非正式团体知识交互网络的描述与分析中提出利用"小世界"的平均路径长度和聚类系数来表征IFG知识交互网络中的交互频繁度和交互聚集度的思想,为进一步研究IFG组织及管理与其内部知识创新的内在联系提供了数量分析基础. 相似文献
35.
含影响力因子的硬聚类算法(HCMef)在对多于两类规模不均的样本进行聚类时,影响力因子指数对聚类结果影响很大,取值不当会引起类消失.影响力因子指数在0附近穷举,并利用影响力因子指数较大时类规模会在较少训练次数内消失的现象,降低计算量.提出了含影响力因子的自适应C均值聚类策略(AHCMef),并介绍了两阶段聚类方法,进一步提高聚类成功率和执行效率.结果显示,最佳影响力因子指数出现在成功聚类时的较大值附近,聚类效果从该点起随影响力因子指数的减小而降低.对HCMef算法应用于多类规模不均样本情况时,影响力因子指数的选取具有指导意义. 相似文献
36.
Jianyong Wang Yuzhou Zhang Lizhu Zhou George Karypis Charu C. Aggarwal 《Data mining and knowledge discovery》2009,18(1):1-29
In recent years we have witnessed several applications of frequent sequence mining, such as feature selection for protein
sequence classification and mining block correlations in storage systems. In typical applications such as clustering, it is
not the complete set but only a subset of discriminating frequent subsequences which is of interest. One approach to discovering
the subset of useful frequent subsequences is to apply any existing frequent sequence mining algorithm to find the complete
set of frequent subsequences. Then, a subset of interesting subsequences can be further identified. Unfortunately, it is very
time consuming to mine the complete set of frequent subsequences for large sequence databases. In this paper, we propose a
new algorithm, CONTOUR, which efficiently mines a subset of high-quality subsequences directly in order to cluster the input
sequences. We mainly focus on how to design some effective search space pruning methods to accelerate the mining process and
discuss how to construct an accurate clustering algorithm based on the result of CONTOUR. We conducted an extensive performance
study to evaluate the efficiency and scalability of CONTOUR, and the accuracy of the frequent subsequence-based clustering
algorithm. 相似文献
37.
Mao-Zu Guo Jun Wang Chun-yu Wang Yang Liu 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2009,13(12):1143-1151
TagSNP selection, which aims to select a small subset of informative single nucleotide polymorphisms (SNPs) to represent the
whole large SNP set, has played an important role in current genomic research. Not only can this cut down the cost of genotyping
by filtering a large number of redundant SNPs, but also it can accelerate the study of genome-wide disease association. In
this paper, we propose a new hybrid method called CMDStagger that combines the ideas of the clustering and the graph algorithm,
to find the minimum set of tagSNPs. The proposed algorithm uses the information of the linkage disequilibrium association
and the haplotype diversity to reduce the information loss in tagSNP selection, and has no limit of block partition. The approach
is tested on eight benchmark datasets from Hapmap and chromosome 5q31. Experimental results show that the algorithm in this
paper can reduce the selection time and obtain less tagSNPs with high prediction accuracy. It indicates that this method has
better performance than previous ones. 相似文献
38.
Isaac J. Sledge Timothy C. Havens Jacalyn M. Huband James C. Bezdek James M. Keller 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2009,13(12):1125-1142
As humans, we have innate faculties that allow us to efficiently segment groups of objects. Computers, to some degree, can
be programmed with similar categorical capabilities, which stem from exploratory data analysis. Out of the various subsets
of data reasoning, clustering provides insight into the structure and relationships of input samples situated in a number
of distributions. To determine these relationships, many clustering methods rely on one or more human inputs; the most important
being the number of distributions, c, to seek. This work investigates a technique for estimating the number of clusters from a general type of data called relational
data. Several numerical examples are presented to illustrate the effectiveness of the proposed method. 相似文献
39.
Efrat Blumenfeld-Lieberthal 《Networks and Spatial Economics》2009,9(3):427-458
This paper presents an analysis of the topology of transportation networks within different systems of cities. Urban entities
and their components are complex systems by their nature; there is no central force that affects their spatial structure.
Thus, we study transportation networks within different countries as complex networks. Based on the above, we consider cities
as nodes, while direct air and railways routes represent the links. We present characteristics of these networks including
their degree and clustering coefficient. Transportation networks can be used as an indicator of economic activity between
cities. Cities with strong economic relationship are characterized by high volume of connectivity. Our findings suggest that
the topology of the analyzed transportation networks can be used to classify the countries they belong to based on their economic
development.
相似文献
Efrat Blumenfeld-LieberthalEmail: |
40.