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1.
We consider parametric optimization problems from an algebraic viewpoint. The idea is to find all of the critical points of an objective function thereby determining a global optimum. For generic parameters (data) in the objective function the number of critical points remains constant. This number is known as the algebraic degree of an optimization problem. In this article, we go further by considering the inverse problem of finding parameters of the objective function so it gives rise to critical points exhibiting a special structure. For example if the critical point is in the singular locus, has some symmetry, or satisfies some other algebraic property. Our main result is a theorem describing such parameters.  相似文献   
2.
Organic solar cells (OSCs) harvesting indoor light are highly promising for emerging technologies, such as internet of things. Herein, the photovoltaic performance of PTB7-Th:PC71BM solar cells constructed using “optimized (with 1,8-diiodooctane (DIO))” and “non-optimized (without DIO)” processing conditions are compared for indoor and outdoor applications. We find that in comparison to the “optimized” solar cell, the “non-optimized” solar cell is less efficient under simulated solar light illumination (100 mW cm−2, spectral range 350–1100 nm), owing to significant bimolecular charge carrier recombination losses. However, under simulated indoor illumination (3.28 mW cm−2, spectral range 400–700 nm), bimolecular recombination losses are effective suppressed, thus the power conversion efficiency of the solar cell without DIO was increased to 14.7 %, higher than that of the solar cell with DIO (14.2 %). These results suggest that the common strategy used to optimize the OSCs could be undesired for indoor OSCs. We demonstrate that the efforts for realizing the desired “morphology” of the active layer for the outdoor OSCs may be unnecessary for indoor OSCs, allowing us to realize high-efficiency indoor OSCs using a non-halogenated solvent.  相似文献   
3.
Herein, we investigated the analytical features of potentiometric immunosensors for detection of alpha-fetoprotein (AFP) in hepatocellular carcinoma at different electrodes, such as carbon fiber microelectrode (CFME) and carbon-disk electrode (CDE), respectively. To construct such an immunosensor, anti-AFP capture antibodies were first conjugated covalently onto the activated electrodes through typical carbodiimide coupling. Thereafter, one-step immunoreaction protocol was successfully introduced to develop a new potentiometric immunoassay upon addition of AFP. Accompanying the antigen-antibody reaction, the surface charges of the modified electrodes were changed for the readout of electric potential. Results indicated that the linear range of CDE-based immunosensor was 0.1–100 ng mL−1 AFP, whereas the assay sensitivity by using CFME could be further increased to 3.2 pg mL−1 with the linear range from 0.01 to 500 ng mL−1 AFP. Meanwhile, CFME-based immunosensor showed high sensitivity, good reproducibility and specificity, and could be utilized for the analysis of human serum specimens with consistent results relative to commercialized ELISA kit.  相似文献   
4.
One of the major capacity boosters for 5G networks is the deployment of ultra-dense heterogeneous networks (UDHNs). However, this deployment results in a tremendous increase in the energy consumption of the network due to the large number of base stations (BSs) involved. In addition to enhanced capacity, 5G networks must also be energy efficient for it to be economically viable and environmentally friendly. Dynamic cell switching is a very common way of reducing the total energy consumption of the network, but most of the proposed methods are computationally demanding, which makes them unsuitable for application in ultra-dense network deployment with massive number of BSs. To tackle this problem, we propose a lightweight cell switching scheme also known as Threshold-based Hybrid cEll swItching Scheme (THESIS) for energy optimization in UDHNs. The developed approach combines the benefits of clustering and exhaustive search (ES) algorithm to produce a solution whose optimality is close to that of the ES (which is guaranteed to be optimal), but is computationally more efficient than ES and as such can be applied for cell switching in real networks even when their dimension is large. The performance evaluation shows that THESIS significantly reduces the energy consumption of the UDHN and can reduce the complexity of finding a near-optimal solution from exponential to polynomial complexity.  相似文献   
5.
为克服机器学习方法在油藏单井产量预测中的过拟合问题, 提高油田生产中的产量预测精度, 提出一种基于条件生成式对抗网络(CGAN)的油藏单井产量预测模型。该模型使用长短期记忆、全连接等基础神经网络, 构建生成和判别网络模型。生成网络模型以产量影响因素为条件输入, 生成预测产量数据, 利用对数损失函数评价预测数据与真实数据之间的偏差, 通过条件生成式对抗网络的博弈训练, 并结合贝叶斯超参数优化算法, 优化模型结构, 综合提高模型的泛化能力。基于Eclipse数值模拟软件建立同一井网条件下不同地质和生产条件下的油藏单井产量数据库, 以地质与生产条件等产量影响因素作为模型的条件输入, 进行油藏单井产量预测。结果表明: 与全连接神经网络(FCNN)、随机森林(RF)以及长短期记忆神经网络(LSTM)模型的预测结果相比, CGAN模型在测试集上的平均绝对百分比误差分别提升了2.59%、0.81%以及1.72%, 并且过拟合比最小(1.027)。说明CGAN降低了机器学习产量预测模型的过拟合程度, 提高了模型的泛化能力与预测精度, 验证了所提算法的优越性, 对指导油田高效开发和保障我国能源战略安全具有重要意义。  相似文献   
6.
This paper considers a multi-user wireless communication network supported by a multiple-antenna base station (BS), where the users who are located sufficiently close to the BS employ wireless energy harvesting (EH) to replenish their energy needs. The objective of this work is to design an efficient beamforming to maximize the minimum throughput among all the information users (IUs), subject to EH constraints. In this regard, transmit time-switching approach is employed, where energy and information are transmitted over different fractions of a time-slot. To achieve efficient EH, a conjugate beamforming (matched filtering) is applied. To design efficient information beamforming for max–min throughput optimization, conventional zero-forcing (ZF) beamforming can be adopted, however, it will not suppress multi-user interference if the number of users is greater than the number of antennas at the BS. To this end, different from the existing works which employ regularized zero-forcing (RZF) beamforming, this work proposes a new generalized zero-forcing (GZF) beamforming, which promises better max–min throughput compared to that achieved by the RZF beamforming. A new path-following algorithm is developed to achieve max–min throughput optimization by GZF beamforming, which is based on a simple convex quadratic program over each iteration.  相似文献   
7.
土壤硝态氮反映土壤短期氮素供应水平,实时了解土壤硝态氮的含量为精准农业和农业面源污染防控提供支撑,因此,在线实时检测土壤硝态氮方法突破就显得十分迫切。土壤硝态氮中的硝酸根离子在土壤中的高水溶性和流动性为全固态硝酸根离子选择电极高敏感检测土壤中硝态氮提供了条件,固态硝态氮离子选择电极的离子选择膜反应硝酸根离子在被测溶液中的浓度。采用全固态硝酸根离子选择电极,且与温度电极和pH电极融合组成电极阵列对土壤饱和溶液中的硝态根离子进行检测。设计了高输入阻抗运算放大电路对电极信号进行采集,并通过微处理控制蠕动泵完成土壤硝态氮待测溶液连续流动测量及实时传输结果。实验结果表明,电极响应时间≤15 s,斜率-51.63 mV/decade,线性范围10-5-10-2.2 mol/L,最低检测限10-5.23 mol/L。相对标准差在0.78%-4.47%范围内,加标回收率均在90%-110%以内。与国家标准紫外可见分光光度法测试结果相比,相关系数(R2)为0.9952,为土壤硝态氮在现场检测奠定技术基础。  相似文献   
8.
This review summarizes recent progress in understanding the oxygen reduction and evolution reactions at the lanthanum strontium manganite electrode of a high-temperature solid oxide cell. Information provided here is put into the perspective of the defect chemistry of lanthanum strontium manganite and its impact on the electrode reaction mechanisms itself. After summarizing recent views on the oxygen reduction reaction mechanism, the focus turns to the oxygen evolution reaction, which is significantly less treated in the literature. A combination of the information in the literature on both reactions was the basis for modified reaction mechanism of the oxygen evolution reaction to be proposed under consideration of recent experimental observations and theoretical findings.  相似文献   
9.
本文研究滚装码头混合泊位分配和劳动力分配的联合调度优化问题。首先,考虑潮汐时间窗约束、装卸劳动力约束、泊位缆桩分布约束以及泊位不规则布局因素,建立以最小化船舶总服务时间为目标的混合整数规划模型。其次,采用内外嵌套算法设计策略,提出求解该类问题的组合算法。其中,外层是多种群并行进化的遗传算法,生成多种船舶计划顺序,内层为基于规则的启发式算法,用于计算给定计划顺序的目标函数值。然后,基于实际运营数据,生成多组不同规模的算例进行全面数值实验,结果表明所提出的算法可在10分钟内求解包含50艘船、100个泊段的算例。最后,开展基于真实滚装码头运营实例的案例分析,对所提模型和算法在实际码头调度问题中的适用性与高效性进行验证。  相似文献   
10.
We consider an intelligent reflecting surface (IRS)-assisted wireless powered communication network (WPCN) in which a multi antenna power beacon (PB) sends a dedicated energy signal to a wireless powered source. The source first harvests energy and then utilizing this harvested energy, it sends an information signal to destination where an external interference may also be present. For the considered system model, we formulated an analytical problem in which the objective is to maximize the throughput by jointly optimizing the energy harvesting (EH) time and IRS phase shift matrices. The optimization problem is high dimensional non-convex, thus a good quality solution can be obtained by invoking any state-of-the-art algorithm such as Genetic algorithm (GA). It is well-known that the performance of GA is generally remarkable, however it incurs a high computational complexity. To this end, we propose a deep unsupervised learning (DUL) based approach in which a neural network (NN) is trained very efficiently as time-consuming task of labeling a data set is not required. Numerical examples show that our proposed approach achieves a better performance–complexity trade-off as it is not only several times faster but also provides almost same or even higher throughput as compared to the GA.  相似文献   
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