全文获取类型
收费全文 | 42789篇 |
免费 | 6546篇 |
国内免费 | 3075篇 |
专业分类
电工技术 | 3041篇 |
技术理论 | 2篇 |
综合类 | 3751篇 |
化学工业 | 3308篇 |
金属工艺 | 1105篇 |
机械仪表 | 3364篇 |
建筑科学 | 1595篇 |
矿业工程 | 452篇 |
能源动力 | 979篇 |
轻工业 | 1005篇 |
水利工程 | 563篇 |
石油天然气 | 487篇 |
武器工业 | 363篇 |
无线电 | 5793篇 |
一般工业技术 | 1699篇 |
冶金工业 | 829篇 |
原子能技术 | 275篇 |
自动化技术 | 23799篇 |
出版年
2024年 | 52篇 |
2023年 | 437篇 |
2022年 | 899篇 |
2021年 | 1108篇 |
2020年 | 1071篇 |
2019年 | 897篇 |
2018年 | 968篇 |
2017年 | 831篇 |
2016年 | 986篇 |
2015年 | 942篇 |
2014年 | 4674篇 |
2013年 | 3696篇 |
2012年 | 4617篇 |
2011年 | 5373篇 |
2010年 | 4361篇 |
2009年 | 4081篇 |
2008年 | 2568篇 |
2007年 | 2043篇 |
2006年 | 1867篇 |
2005年 | 1763篇 |
2004年 | 1480篇 |
2003年 | 1393篇 |
2002年 | 1185篇 |
2001年 | 927篇 |
2000年 | 780篇 |
1999年 | 747篇 |
1998年 | 584篇 |
1997年 | 520篇 |
1996年 | 395篇 |
1995年 | 304篇 |
1994年 | 213篇 |
1993年 | 182篇 |
1992年 | 135篇 |
1991年 | 65篇 |
1990年 | 60篇 |
1989年 | 45篇 |
1988年 | 29篇 |
1987年 | 20篇 |
1986年 | 24篇 |
1985年 | 18篇 |
1984年 | 18篇 |
1983年 | 15篇 |
1982年 | 9篇 |
1981年 | 8篇 |
1980年 | 7篇 |
1979年 | 5篇 |
1977年 | 3篇 |
1976年 | 1篇 |
1974年 | 2篇 |
1972年 | 1篇 |
排序方式: 共有10000条查询结果,搜索用时 15 毫秒
1.
死亡风险预测指根据病人临床体征监测数据来预测未来一段时间的死亡风险。对于ICU病患,通过死亡风险预测可以有针对性地对病人做出临床诊断,以及合理安排有限的医疗资源。基于临床使用的MEWS和Glasgow昏迷评分量表,针对ICU病人临床监测的17项生理参数,提出一种基于多通道的ICU脑血管疾病死亡风险预测模型。引入多通道概念应用于BiLSTM模型,用于突出每个生理参数对死亡风险预测的作用。采用Attention机制用于提高模型预测精度。实验数据来自MIMIC [Ⅲ]数据库,从中提取3?080位脑血管疾病患者的16?260条记录用于此次研究,除了六组超参数实验之外,将所提模型与LSTM、Multichannel-BiLSTM、逻辑回归(logistic regression)和支持向量机(support vector machine, SVM)四种模型进行了对比分析,准确率Accuracy、灵敏度Sensitive、特异性Specificity、AUC-ROC和AUC-PRC作为评价指标,实验结果表明,所提模型性能优于其他模型,AUC值达到94.3%。 相似文献
2.
Accurate and timely network traffic measurement is essential for network status monitoring, network fault analysis, network intrusion detection, and network security management. With the rapid development of the network, massive network traffic brings severe challenges to network traffic measurement. However, existing measurement methods suffer from many limitations for effectively recording and accurately analyzing big-volume traffic. Recently, sketches, a family of probabilistic data structures that employ hashing technology for summarizing traffic data, have been widely used to solve these problems. However, current literature still lacks a thorough review on sketch-based traffic measurement methods to offer a comprehensive insight on how to apply sketches for fulfilling various traffic measurement tasks. In this paper, we provide a detailed and comprehensive review on the applications of sketches in network traffic measurement. To this end, we classify the network traffic measurement tasks into four categories based on the target of traffic measurement, namely cardinality estimation, flow size estimation, change anomaly detection, and persistent spreader identification. First, we briefly introduce these four types of traffic measurement tasks and discuss the advantages of applying sketches. Then, we propose a series of requirements with regard to the applications of sketches in network traffic measurement. After that, we perform a fine-grained classification for each sketch-based measurement category according to the technologies applied on sketches. During the review, we evaluate the performance, advantages and disadvantages of current sketch-based traffic measurement methods based on the proposed requirements. Through the thorough review, we gain a number of valuable implications that can guide us to choose and design proper traffic measurement methods based on sketches. We also review a number of general sketches that are highly expected in modern network systems to simultaneously perform multiple traffic measurement tasks and discuss their performance based on the proposed requirements. Finally, through our serious review, we summarize a number of open issues and identify several promising research directions. 相似文献
3.
Zhenkun Ke Xin Cao Chuanli Shan Lifen Shi Pingping Wang Yong Yang Fengyang Zhao Jiedong Cui Jinwei Li Gang Zhou Min Guan Tao Yu 《Ceramics International》2021,47(14):19605-19613
The purpose of the current work was to research the effect of alkali metal oxide on the structure, thermal properties, viscosity and chemical stability in the glass system (R2O–CaO–B2O3–SiO2) systematically. Because the glass would emulsify when Li2O was added to the glass batch, this article did not discuss Li2O. The results showed that when the amount of Na2O was less than 4 mol.%, there was a higher interconnectivity of borate and silicate sub-networks in glass, as more mixed Si–O–B bonds were present in glass. The glass samples exhibited excellent thermal properties and chemical stabilities. As the amount of Na2O exceeded 4 mol.%, the interconnectivity of borate and silicate sub-networks was weakened. The thermal properties and chemical stabilities of the glass samples were reduced. The connectivity of the silicate sub-network was weakened slightly as the Na/K ratio varied, and the coefficient of thermal expansion (CTE) of the glass samples gradually increased, and the resistance to thermal shock (RTS) value gradually decreased. Moreover, the viscosity of the glass samples decreased with the ratio of Na/Si and Na/K increased. 相似文献
4.
Face aging (FA) for young faces refers to rendering the aging faces at target age for an individual, generally under 20s, which is an important topic of facial age analysis. Unlike traditional FA for adults, it is challenging to age children with one deep learning-based FA network, since there are deformations of facial shapes and variations of textural details. To alleviate the deficiency, a unified FA framework for young faces is proposed, which consists of two decoupled networks to apply aging image translation. It explicitly models transformations of geometry and appearance using two components: GD-GAN, which simulates the Geometric Deformation using Generative Adversarial Network; TV-GAN, which simulates the Textural Variations guided by the age-related saliency map. Extensive experiments demonstrate that our method has advantages over the state-of-the-art methods in terms of synthesizing visually plausible images for young faces, as well as preserving the personalized features. 相似文献
5.
6.
As the first review in this field, this paper presents an in-depth mathematical view of Intelligent Flight Control Systems (IFCSs), particularly those based on artificial neural networks. The rapid evolution of IFCSs in the last two decades in both the methodological and technical aspects necessitates a comprehensive view of them to better demonstrate the current stage and the crucial remaining steps towards developing a truly intelligent flight management unit. To this end, in this paper, we will provide a detailed mathematical view of Neural Network (NN)-based flight control systems and the challenging problems that still remain. The paper will cover both the model-based and model-free IFCSs. The model-based methods consist of the basic feedback error learning scheme, the pseudocontrol strategy, and the neural backstepping method. Besides, different approaches to analyze the closed-loop stability in IFCSs, their requirements, and their limitations will be discussed in detail. Various supplementary features, which can be integrated with a basic IFCS such as the fault-tolerance capability, the consideration of system constraints, and the combination of NNs with other robust and adaptive elements like disturbance observers, would be covered, as well. On the other hand, concerning model-free flight controllers, both the indirect and direct adaptive control systems including indirect adaptive control using NN-based system identification, the approximate dynamic programming using NN, and the reinforcement learning-based adaptive optimal control will be carefully addressed. Finally, by demonstrating a well-organized view of the current stage in the development of IFCSs, the challenging issues, which are critical to be addressed in the future, are thoroughly identified. As a result, this paper can be considered as a comprehensive road map for all researchers interested in the design and development of intelligent control systems, particularly in the field of aerospace applications. 相似文献
7.
The aim of the research is evaluating the classification performances of eight different machine-learning methods on the antepartum cardiotocography (CTG) data. The classification is necessary to predict newborn health, especially for the critical cases. Cardiotocography is used for assisting the obstetricians’ to obtain detailed information during the pregnancy as a technique of measuring fetal well-being, essentially in pregnant women having potential complications. The obstetricians describe CTG shortly as a continuous electronic record of the baby's heart rate took from the mother's abdomen. The acquired information is necessary to visualize unhealthiness of the embryo and gives an opportunity for early intervention prior to happening a permanent impairment to the embryo. The aim of the machine learning methods is by using attributes of data obtained from the uterine contraction (UC) and fetal heart rate (FHR) signals to classify as pathological or normal. The dataset contains 1831 instances with 21 attributes, examined by applying the methods. In the paper, the highest accuracy displayed as 99.2%. 相似文献
8.
利用计算机实现自动、准确的秀丽隐杆线虫(C.elegans)的各项形态学参数分析,至关重要的是从显微图像上分割出线虫体态,但由于显微镜下的图像噪声较多,线虫边缘像素与周围环境相似,而且线虫的体态具有鞭毛和其他附着物需要分离,多方面因素导致设计一个鲁棒性的C.elegans分割算法仍然面临着挑战。针对这些问题,提出了一种基于深度学习的线虫分割方法,通过训练掩模区域卷积神经网络(Mask R-CNN)学习线虫形态特征实现自动分割。首先,通过改进多级特征池化将高级语义特征与低级边缘特征融合,结合大幅度软最大损失(LMSL)损失算法改进损失计算;然后,改进非极大值抑制;最后,引入全连接融合分支等方法对分割结果进行进一步优化。实验结果表明,相比原始的Mask R-CNN,该方法平均精确率(AP)提升了4.3个百分点,平均交并比(mIOU)提升了4个百分点。表明所提出的深度学习分割方法能够有效提高分割准确率,在显微图像中更加精确地分割出线虫体。 相似文献
9.
在无线传感器网络中,大量感知数据汇集到sink节点的采集方法会导致sink节点附近的节点能量耗尽,造成能量空洞。针对该问题,利用移动的sink节点进行数据收集是一种解决方法,其中移动sink的路径规划成为一个重要的问题。提出了一个移动sink路径规划算法,将无线传感器中随机分布的节点划分为不同的子区域,寻找sink节点移动的最佳转向点,最终得到最优的移动路径,以实现无线传感器网络生命周期最大化。仿真实验表明,与现有方案相比,该算法能显著延长网络的生命周期。 相似文献
10.
In this paper, novel computing approach using three different models of feed-forward artificial neural networks (ANNs) are presented for the solution of initial value problem (IVP) based on first Painlevé equation. These mathematical models of ANNs are developed in an unsupervised manner with capability to satisfy the initial conditions exactly using log-sigmoid, radial basis and tan-sigmoid transfer functions in hidden layers to approximate the solution of the problem. The training of design parameters in each model is performed with sequential quadratic programming technique. The accuracy, convergence and effectiveness of the proposed schemes are evaluated on the basis of the results of statistical analyses through sufficient large number of independent runs with different number of neurons in each model as well. The comparisons of these results of proposed schemes with standard numerical and analytical solutions validate the correctness of the design models. 相似文献