全文获取类型
收费全文 | 48451篇 |
免费 | 5285篇 |
国内免费 | 3473篇 |
专业分类
电工技术 | 2291篇 |
技术理论 | 5篇 |
综合类 | 4192篇 |
化学工业 | 5716篇 |
金属工艺 | 550篇 |
机械仪表 | 1438篇 |
建筑科学 | 3817篇 |
矿业工程 | 821篇 |
能源动力 | 1928篇 |
轻工业 | 2019篇 |
水利工程 | 4851篇 |
石油天然气 | 3359篇 |
武器工业 | 174篇 |
无线电 | 6070篇 |
一般工业技术 | 2810篇 |
冶金工业 | 702篇 |
原子能技术 | 385篇 |
自动化技术 | 16081篇 |
出版年
2024年 | 206篇 |
2023年 | 832篇 |
2022年 | 1242篇 |
2021年 | 1525篇 |
2020年 | 1587篇 |
2019年 | 1442篇 |
2018年 | 1242篇 |
2017年 | 1535篇 |
2016年 | 1812篇 |
2015年 | 1988篇 |
2014年 | 2860篇 |
2013年 | 3117篇 |
2012年 | 3409篇 |
2011年 | 3539篇 |
2010年 | 2752篇 |
2009年 | 3070篇 |
2008年 | 3062篇 |
2007年 | 3302篇 |
2006年 | 2994篇 |
2005年 | 2483篇 |
2004年 | 2029篇 |
2003年 | 1744篇 |
2002年 | 1603篇 |
2001年 | 1351篇 |
2000年 | 1188篇 |
1999年 | 981篇 |
1998年 | 807篇 |
1997年 | 682篇 |
1996年 | 581篇 |
1995年 | 444篇 |
1994年 | 392篇 |
1993年 | 307篇 |
1992年 | 254篇 |
1991年 | 181篇 |
1990年 | 140篇 |
1989年 | 117篇 |
1988年 | 67篇 |
1987年 | 46篇 |
1986年 | 34篇 |
1985年 | 67篇 |
1984年 | 54篇 |
1983年 | 43篇 |
1982年 | 46篇 |
1981年 | 10篇 |
1980年 | 7篇 |
1979年 | 8篇 |
1978年 | 3篇 |
1977年 | 4篇 |
1959年 | 5篇 |
1951年 | 4篇 |
排序方式: 共有10000条查询结果,搜索用时 250 毫秒
1.
A key element in solving real-life data science problems is selecting the types of models to use. Tree ensemble models (such as XGBoost) are usually recommended for classification and regression problems with tabular data. However, several deep learning models for tabular data have recently been proposed, claiming to outperform XGBoost for some use cases. This paper explores whether these deep models should be a recommended option for tabular data by rigorously comparing the new deep models to XGBoost on various datasets. In addition to systematically comparing their performance, we consider the tuning and computation they require. Our study shows that XGBoost outperforms these deep models across the datasets, including the datasets used in the papers that proposed the deep models. We also demonstrate that XGBoost requires much less tuning. On the positive side, we show that an ensemble of deep models and XGBoost performs better on these datasets than XGBoost alone. 相似文献
2.
Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method. 相似文献
3.
Tongling Xia Yue Qi Xilei Dai Jinyu Liu Can Xiao Ruoyu You Dayi Lai Junjie Liu Chun Chen 《Indoor air》2021,31(6):2020-2032
To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM2.5 monitoring using low-cost light-scattering sensors. 相似文献
4.
Thomas R. Savage Fernando Almeida-Trasvina Ehecatl A. del-Rio Chanona Robin Smith Dondga Zhang 《American Institute of Chemical Engineers》2021,67(11):e17358
With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems. 相似文献
5.
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
6.
Topic modeling is a popular analytical tool for evaluating data. Numerous methods of topic modeling have been developed which consider many kinds of relationships and restrictions within datasets; however, these methods are not frequently employed. Instead many researchers gravitate to Latent Dirichlet Analysis, which although flexible and adaptive, is not always suited for modeling more complex data relationships. We present different topic modeling approaches capable of dealing with correlation between topics, the changes of topics over time, as well as the ability to handle short texts such as encountered in social media or sparse text data. We also briefly review the algorithms which are used to optimize and infer parameters in topic modeling, which is essential to producing meaningful results regardless of method. We believe this review will encourage more diversity when performing topic modeling and help determine what topic modeling method best suits the user needs. 相似文献
7.
Most real-world vehicle nodes can be structured into an interconnected network of vehicles. Through structuring these services and vehicle device interactions into multiple types, such internet of vehicles becomes multidimensional heterogeneous overlay networks. The heterogeneousness of the overlays makes it difficult for the overlay networks to coordinate with each other to improve their performance. Therefore, it poses an interesting but critical challenge to the effective analysis of heterogeneous virtual vehicular networks. A variety of virtual vehicular networks can be easily deployed onto the native network by applying the concept of SDN (Software Defined Networking). These virtual networks reflect their heterogeneousness due to their different performance goals, and they compete for the same physical resources of the underlying network, so that a sub-optimal performance of the virtual networks may be achieved. Therefore, we propose a Deep Reinforcement Learning (DRL) approach to make the virtual networks cooperate with each other through the SDN controller. A cooperative solution based on the asymmetric Nash bargaining is proposed for co-existing virtual networks to improve their performance. Moreover, the Markov Chain model and DRL resolution are introduced to leverage the heterogeneous performance goals of virtual networks. The implementation of the approach is introduced, and simulation results confirm the performance improvement of the latency sensitive, loss-rate sensitive and throughput sensitive heterogeneous vehicular networks using our cooperative solution. 相似文献
8.
9.
Several three-party password authenticated key exchange (3-PAKE) protocols have recently been proposed for heterogeneous wireless sensor networks (HWSN). These are efficient and designed to address security concerns in ad-hoc sensor network applications for a global Internet of Things framework, where a user may request access to sensitive information collected by resource-constrained sensors in clusters managed by gateway nodes. In this paper we first analyze three recently proposed 3-PAKE protocols and discuss their vulnerabilities. Then, based on Radio Frequency Identification technologies we propose a novel 3-PAKE protocol for HWSN applications, with two extensions for additional security features, that is provably secure, efficient and flexible. 相似文献
10.
Aditi Chatterjee Jayabrata Biswas Kiranmoy Das 《International Journal of Communication Systems》2020,33(9)
In recent years, Internet of Things (IoT) devices are used for remote health monitoring. For remotely monitoring a patient, only the health information at different time points are not sufficient; predicted values of biomarkers (for some future time points) are also important. In this article, we propose a powerful statistical model for an efficient dynamic patient monitoring using wireless sensor nodes through Bayesian Learning (BL). We consider the setting where a set of correlated biomarkers are measured from a patient through wireless sensors, but the sensors only report the ordinal outcomes (say, good, fair, high, or very high) to the sink based on some prefixed thresholds. The challenge is to use the ordinal outcomes for monitoring and predicting the health status of the patient under consideration. We propose a linear mixed model where interbiomarker correlations and intrabiomarker dependence are modeled simultaneously. The estimated and the predicted values of the biomarkers are transferred over the internet so that health care providers and the family members of the patient can remotely monitor the patient. Extensive simulation studies are performed to assess practical usefulness of our proposed joint model, and the performance of the proposed joint model is compared to that of some other traditional models used in the literature. 相似文献