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991.
    
With the popularity of green computing and the huge usage of networks, there is an acute need for expansion of the 5G network. 5G is used where energy efficiency is the highest priority, and it can play a pinnacle role in helping every industry to hit sustainability. While in the 5G network, conventional performance guides, such as network capacity and coverage are still major issues and need improvements. Device to Device communication (D2D) communication technology plays an important role to improve the capacity and coverage of 5G technology using different techniques. The issue of energy utilization in the IoT based system is a significant exploration center. Energy optimization in D2D communication is an important point. We need to resolve this issue for increasing system performance. Green IoT speaks to the issue of lessening energy utilization of IoT gadgets which accomplishes a supportable climate for IoT systems. In this paper, we improve the capacity and coverage of 5G technology using Multiple Inputs Multiple Outputs (MU-MIMO). MU-MIMO increases the capacity of 5G in D2D communication. We also present all the problems faced by 5G technology and proposed architecture to enhance system performance.  相似文献   
992.
    
Aqueous zinc-ion batteries have been regarded as a promising alternative to large-scale energy storage, due to associated low-cost, improved safety and environmental friendliness. However, a high-performance cathode material for both rate capability and specific capacity is still a challenge. One kind of the more promising candidates are sodium manganese oxide (NMO) materials, although they suffer from individual issues and need to be further improved. Herein, we present a novel mixed phase NMO material composed of nearly equal amounts of Na0.55Mn2O4 and Na0.7MnO2.05. The structured configuration with particle size of 200–500 nm is found to be beneficial towards improving the ion diffusion rate during the charge/discharge process. Compared with Na0.7MnO2.05 and Na0.55Mn2O4, the mixed phase NMO demonstrates an enhanced rate capability and excellent long-term cycling stability with a capacity retention of 83% after 800 cycles. More importantly, the system also delivers an impressive energy density and power density, as 378 W·h·kg−1 at 68.7 W·kg−1, or 172 W·h·kg−1 at 1705 W·kg−1. The superior electrochemical performance is ascribed to the fast Zn2+ diffusion rate because of a large ratio of capacitive contribution (63.9% at 0.9 mV·s−1). Thus, the mixed phase route provides a novel strategy to enhance electrochemical performance, enabling mixed phase NMO as very promising material towards large-scale energy-storage applications.  相似文献   
993.
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This paper provides an attempt to utilize machine learning algorithm, explicitly random-forest algorithm, to optimize the performance of dye sensitized solar cells (DSSCs) in terms of conversion efficiency. The optimization is implemented with respect to both the mesoporous TiO2 active layer thickness and porosity. Herein, the porosity impact is reflected to the model as a variation in the effective refractive index and dye absorption. Database set has been established using our data in the literature as well as numerical data extracted from our numerical model. The random-forest model is used for model regression, prediction, and optimization, reaching 99.87% accuracy. Perfect agreement with experimental data was observed, with 4.17% conversion efficiency.  相似文献   
994.
    
In the Smart Grid (SG) residential environment, consumers change their power consumption routine according to the price and incentives announced by the utility, which causes the prices to deviate from the initial pattern. Thereby, electricity demand and price forecasting play a significant role and can help in terms of reliability and sustainability. Due to the massive amount of data, big data analytics for forecasting becomes a hot topic in the SG domain. In this paper, the changing and non-linearity of consumer consumption pattern complex data is taken as input. To minimize the computational cost and complexity of the data, the average of the feature engineering approaches includes: Recursive Feature Eliminator (RFE), Extreme Gradient Boosting (XGboost), Random Forest (RF), and are upgraded to extract the most relevant and significant features. To this end, we have proposed the DensetNet-121 network and Support Vector Machine (SVM) ensemble with Aquila Optimizer (AO) to ensure adaptability and handle the complexity of data in the classification. Further, the AO method helps to tune the parameters of DensNet (121 layers) and SVM, which achieves less training loss, computational time, minimized overfitting problems and more training/test accuracy. Performance evaluation metrics and statistical analysis validate the proposed model results are better than the benchmark schemes. Our proposed method has achieved a minimal value of the Mean Average Percentage Error (MAPE) rate i.e., 8% by DenseNet-AO and 6% by SVM-AO and the maximum accurateness rate of 92% and 95%, respectively.  相似文献   
995.
    
Selective laser melting (SLM) is a mainstream powder-bed fusion additive manufacturing (AM) process that creates a three-dimensional (3D) object using a high power laser to fuse fine particles of various metallic powders such as copper, tool steel, cobalt chrome, titanium, tungsten, aluminium and stainless steel. Over the past decade, SLM has received significant attention due to its capability in producing dense parts with superior mechanical properties. As a premier shape memory alloy, the nickel-titanium (NiTi) shape memory alloy is attractive for a variety of biomedical applications due to its superior mechanical properties, superelasticity, corrosion resistance and biocompatibility. This paper presents a comprehensive review of the recent progress in NiTi alloys produced by the SLM process, with a particular focus on the relationship between processing parameters, resultant microstructures and properties. Current research gaps, challenges and suggestions for future research are also addressed.The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-021-00376-9  相似文献   
996.
    
The networks are fundamental to our modern world and they appear throughout science and society. Access to a massive amount of data presents a unique opportunity to the researcher’s community. As networks grow in size the complexity increases and our ability to analyze them using the current state of the art is at severe risk of failing to keep pace. Therefore, this paper initiates a discussion on graph signal processing for large-scale data analysis. We first provide a comprehensive overview of core ideas in Graph signal processing (GSP) and their connection to conventional digital signal processing (DSP). We then summarize recent developments in developing basic GSP tools, including methods for graph filtering or graph learning, graph signal, graph Fourier transform (GFT), spectrum, graph frequency, etc. Graph filtering is a basic task that allows for isolating the contribution of individual frequencies and therefore enables the removal of noise. We then consider a graph filter as a model that helps to extend the application of GSP methods to large datasets. To show the suitability and the effeteness, we first created a noisy graph signal and then applied it to the filter. After several rounds of simulation results. We see that the filtered signal appears to be smoother and is closer to the original noise-free distance-based signal. By using this example application, we thoroughly demonstrated that graph filtration is efficient for big data analytics.  相似文献   
997.
    
Iraq experiences housing shortage of around1–1.5 million units with low production rate. Managing this challenge requires integrated efforts across a number of fields. One way for ward is to develop an integral and appropriate architectural solution. In Iraq,it remains unknown which of the possible architectural approaches is adequate to address its housing challenges while considering occupants' preferences. Aiming at helping in forming a solution, this study critically assesses the possible building patterns and construction approaches, whichrep resent the main architectural solutions' framework. To achieve this aim, an extensive literature review was conducted that explores possible alternatives and housing requirements. Alternatives were assessed by comparing and contrasting their adequacy in satisfying Iraqis' preferences and the housing sector requirements. The assessment included conducting two surveys: a public Iraqis survey and an experts survey. The former was used to determine Iraqis' residential priorities and the latter to evaluate the adequacy of the defined alternatives in satisfying a set of housing requirements. A total number of 410 Iraqis participated in the first survey and fourteen Iraqi experts in the second. Based on the results, this paper suggests mass construction of multifamily courtyard residential buildings as a solution and discusses future research efforts.  相似文献   
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999.
1000.
Transfer functions of evanescent transmission channels are investigated in detail. Based on a Taylor expansion of the corresponding phase and attenuation constants, different characteristic transmission parameters are introduced (or revisited). The steady-state propagation of an RF carrier signal modulated by a narrowband base-band Gaussian pulse in evanescent waveguide sections is then studied. It is shown that temporal pulse compression as well as carrier frequency drift usually accompany such transmissions. It is also shown that under steady-state conditions, conventionally defined transmission velocities are not necessarily restricted to be less than or equal to c (speed of light in free space) as long as they are not related to direct measurements. Only the power coupling accompanying a measurement is responsible for limiting the transmission velocity of the measured physical quantity below or equal to c.  相似文献   
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