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991.
By introducing the rough set theory into the support vector machine (SVM), a rough margin based SVM (RMSVM) is proposed to deal with the overfitting problem due to outliers. Similar to the classical SVM, the RMSVM searches for the separating hyper-plane that maximizes the rough margin, defined by the lower and upper margin. In this way, more data points are adaptively considered rather than the few extreme value points used in the classical SVM. In addition, different support vectors may have different effects on the learning of the separating hyper-plane depending on their positions in the rough margin. Points in the lower margin have more effects than those in the boundary of the rough margin. From experimental results on six benchmark datasets, the classification accuracy of this algorithm is improved without additional computational expense compared with the classical ν-SVM. 相似文献
992.
D. Ortiz-Martínez I. García-Varea F. Casacuberta 《Pattern recognition letters》2008,29(8):1145-PRintPerclntel
Statistical machine translation (SMT) has proven to be an interesting pattern recognition framework for automatically building machine translations systems from available parallel corpora. In the last few years, research in SMT has been characterized by two significant advances. First, the popularization of the so called phrase-based statistical translation models, which allows to incorporate local contextual information to the translation models. Second, the availability of larger and larger parallel corpora, which are composed of millions of sentence pairs, and tens of millions of running words. Since phrase-based models basically consists in statistical dictionaries of phrase pairs, their estimation from very large corpora is a very costly task that yields a huge number of parameters which are to be stored in memory. The handling of millions of model parameters and a similar number of training samples have become a bottleneck in the field of SMT, as well as in other well-known pattern recognition tasks such as speech recognition or handwritten recognition, just to name a few. In this paper, we propose a general framework that deals with the scaling problem in SMT without introducing significant time overhead by means of the combination of different scaling techniques. This new framework is based on the use of counts instead of probabilities, and on the concept of cache memory. 相似文献
993.
基于LS-SVM的非线性多功能传感器信号重构方法研究 总被引:1,自引:1,他引:0
提出了基于最小二乘支持向量机(Least squares support vector machine, LS-SVM)的非线性多功能传感器信号重构方法. 不同于通常采用的经验风险最小化重构方法, 支持向量机(Support vector machine, SVM)是基于结构风险最小化准则的新型机器学习方法, 适用于小样本标定数据情况, 可有效抑制过拟合问题并改善泛化性能. 在SVM基础上, LS-SVM将不等式约束转化为等式约束, 极大地简化了二次规划问题的求解. 研究中通过L-折交叉验证实现调整参数优化, 在两种非线性情况下对多功能传感器的输入信号进行了重构, 实验结果显示重构精度分别达到0.154\%和1.146\%, 表明提出的LS-SVM重构方法具有高可靠性和稳定性, 验证了方法的有效性. 相似文献
994.
995.
Reversible computing is a paradigm where computing models are defined so that they reflect physical reversibility, one of the fundamental microscopic physical property of Nature. In this survey/tutorial paper, we discuss how computation can be carried out in a reversible system, how a universal reversible computer can be constructed by reversible logic elements, and how such logic elements are related to reversible physical phenomena. We shall see that, in reversible systems, computation can often be carried out in a very different manner from conventional (i.e., irreversible) computing systems, and even very simple reversible systems or logic elements have computation- or logical-universality. We discuss these problems based on reversible logic elements/circuits, reversible Turing machines, reversible cellular automata, and some other related models of reversible computing. 相似文献
996.
In this paper, we consider an identical parallel machine scheduling problem with release dates. The objective is to minimize the total weighted completion time. This problem is known to be strongly NP-hard. We propose some dominance properties and two lower bounds. We also present an efficient heuristic. A branch-and-bound algorithm, in which the heuristic, the lower bounds and the dominance properties are incorporated, is proposed and tested on a large set of randomly generated instances. 相似文献
997.
We consider a single machine scheduling problem with simple linear deterioration. Job processing times are assumed to be a simple linear function of a job-dependent growth rate and the job's starting time. We seek an optimal schedule, so as to minimize the total absolute deviation of completion times (TADC). We prove several interesting properties of an optimal schedule, and introduce two efficient heuristics which are tested against a lower bound. 相似文献
998.
This paper considers single-machine scheduling problems with deteriorating jobs, i.e., jobs whose processing times are an increasing function of their starting times. In addition, the jobs are related by a series–parallel graph. It is shown that for the general linear problem to minimize the makespan, polynomial algorithms exist. It is also shown that for the proportional linear problem of minimization of the total weighted completion time, polynomial algorithms exist, too. 相似文献
999.
This paper presents a computer-aided measurement plan (CAMP) for an impeller on a coordinate measurement machine (CMM) with a rotating/tilting probe. The blade surfaces of a machined impeller were measured exactly to secure the machining tolerance and surface finish of the impeller. CMM with a rotating and tilting probe is commonly used for this measurement. However, it is not easy to evaluate all the points on the impeller surfaces due to the time-consuming nature of the CMM measurement. In addition, many points cannot be easily accessed by the CMM probe due to the interference between the probe and the impeller blades. Furthermore, the inherent complexity of the existing teaching operation of a probe using a joystick suggests the necessity of developing a new method for the measurement planning of an impeller. Thus, this paper proposes a CAMP for effectively gauging the inspection points based on the ruled line information of the impeller blade surfaces. The proposed plan partitions the surfaces into several measurement regions based on the ruled lines of a blade surface and the approach vectors of the probe. Finally, a case example for an impeller is presented to demonstrate the effectiveness of the proposed strategy. 相似文献
1000.
It is well recognized that the impact-acoustic emissions contain information that can indicate the presence of the adhesive defects in the bonding structures. In our previous papers, artificial neural network (ANN) was adopted to assess the bonding integrity of the tile–walls with the feature extracted from the power spectral density (PSD) of the impact-acoustic signals acting as the input of classifier. However, in addition to the inconvenience posed by the general drawbacks such as long training time and large number of training samples needed, the performance of the classic ANN classifier is deteriorated by the similar spectral characteristics between different bonding status caused by abnormal impacts. In this paper our previous works was developed by the employment of the least-squares support vector machine (LS-SVM) classifier instead of the ANN to derive a bonding integrity recognition approach with better reliability and enhanced immunity to surface roughness. With the help of the specially designed artificial sample slabs, experiments results obtained with the proposed method are provided and compared with that using the ANN classifier, demonstrating the effectiveness of the present strategy. 相似文献