全文获取类型
收费全文 | 2042篇 |
免费 | 313篇 |
国内免费 | 306篇 |
专业分类
航空 | 1364篇 |
航天技术 | 502篇 |
综合类 | 295篇 |
航天 | 500篇 |
出版年
2024年 | 8篇 |
2023年 | 65篇 |
2022年 | 65篇 |
2021年 | 78篇 |
2020年 | 80篇 |
2019年 | 79篇 |
2018年 | 74篇 |
2017年 | 70篇 |
2016年 | 105篇 |
2015年 | 110篇 |
2014年 | 134篇 |
2013年 | 83篇 |
2012年 | 145篇 |
2011年 | 152篇 |
2010年 | 114篇 |
2009年 | 94篇 |
2008年 | 124篇 |
2007年 | 119篇 |
2006年 | 128篇 |
2005年 | 126篇 |
2004年 | 90篇 |
2003年 | 104篇 |
2002年 | 72篇 |
2001年 | 66篇 |
2000年 | 53篇 |
1999年 | 36篇 |
1998年 | 47篇 |
1997年 | 36篇 |
1996年 | 24篇 |
1995年 | 29篇 |
1994年 | 43篇 |
1993年 | 24篇 |
1992年 | 16篇 |
1991年 | 21篇 |
1990年 | 22篇 |
1989年 | 15篇 |
1988年 | 8篇 |
1987年 | 1篇 |
1984年 | 1篇 |
排序方式: 共有2661条查询结果,搜索用时 15 毫秒
171.
172.
173.
Mourad Lazri Soltane Ameur Yacine Mohia 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2014
In the present paper, an artificial neural network (ANN) based technique has been developed to estimate instantaneous rainfall by using brightness temperature from the IR sensors of SEVIRI radiometer, onboard Meteosat Second Generation (MSG) satellite. The study is carried out over north of Algeria. For estimation of rainfall, weight matrices of two ANNs namely MLP1 and MLP2 are developed. MLP1 is to identify raining or non-raining pixels. When rainy pixels are identified, then for those pixels, instantaneous rainfall is estimated by using MLP2. For identification of raining and non raining pixels, 7 input parameters from the IR sensors are utilized. Corresponding data of raining/non-raining pixels are taken from radar. For instantaneous rainfall estimation, 14 input parameters are utilized, where 7 parameters are information about raining pixels and 7 parameters are related with cloud features. The results obtained show the neural network performs reasonably well. 相似文献
174.
I.L. Babich V.F. BoretskijA.N. Veklich R.V. Semenyshyn 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2014
Optical emission and linear laser absorption spectroscopy techniques were used in investigation of plasma with copper and silver admixture. The method of selection of spectral lines and spectroscopic data with the aim of diagnostics of multicomponent air plasma with two metal vapors admixture was developed. Energy level populations behavior on the Boltzmann plot were used for Cu I and Ag I spectroscopic data selection. In this way the selection of spectroscopic data for some of Cu I and Ag I lines was realized. Stark broadening parameters of Cu I and Ag I were examined. Experimentally obtained temperature and electron density radial distributions were used in the calculation of plasma composition in the assumption of local thermodynamic equilibrium. Linear laser absorption spectroscopy was used to examine the state of plasma. 相似文献
175.
Chae Kyung Sim Huynh Anh Nguyen Le Soojong Pak Hye-In Lee Wonseok Kang Moo-Young Chun Ueejeong Jeong In-Soo Yuk Kang-Min Kim Chan Park Michael D. Pavel Daniel T. Jaffe 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2014
We present a Python-based data reduction pipeline package (PLP) for the Immersion GRating INfrared Spectrograph (IGRINS), an instrument that covers the complete H- and K-bands in one exposure with a spectral resolving power of 40,000. The reduction steps carried out by the PLP include flat-fielding, background removal, order extraction, distortion correction, wavelength calibration, and telluric correction using spectra of A type standard stars. As the spectrograph has no moving parts, the PLP automatically reduces the data using predefined functions for the processes of order extraction, distortion correction, and wavelength calibration. Before the telluric correction of the target spectra, the intrinsic hydrogen absorption features of the standard A star are removed with a Gaussian fitting algorithm. The final result is the flux of the target as a function of wavelength. Users can customize the predefined functions for the extraction of the spectrum from the echellogram and adjust the parameters for the fitting functions for the spectra of celestial objects, using “fine-tuning” options, as necessary. Presently, the PLP produces the best results for point-source targets. 相似文献
176.
Mehdi Eshagh Morteza Ghorbannia 《Advances in Space Research (includes Cospar's Information Bulletin, Space Research Today)》2014
The spatial truncation error (STE) is a significant systematic error in the integral inversion of satellite gradiometric and orbital data to gravity anomalies at sea level. In order to reduce the effect of STE, a larger area than the desired one is considered in the inversion process, but the anomalies located in its central part are selected as the final results. The STE influences the variance of the results as well because the residual vector, which is contaminated with STE, is used for its estimation. The situation is even more complicated in variance component estimation because of its iterative nature. In this paper, we present a strategy to reduce the effect of STE on the a posteriori variance factor and the variance components for inversion of satellite orbital and gradiometric data to gravity anomalies at sea level. The idea is to define two windowing matrices for reducing this error from the estimated residuals and anomalies. Our simulation studies over Fennoscandia show that the differences between the 0.5°×0.5° gravity anomalies obtained from orbital data and an existing gravity model have standard deviation (STD) and root mean squared error (RMSE) of 10.9 and 12.1 mGal, respectively, and those obtained from gradiometric data have 7.9 and 10.1 in the same units. In the case that they are combined using windowed variance components the STD and RMSE become 6.1 and 8.4 mGal. Also, the mean value of the estimated RMSE after using the windowed variances is in agreement with the RMSE of the differences between the estimated anomalies and those obtained from the gravity model. 相似文献
177.
178.
对于日益复杂的信息环境和变化的目标特性,现有的多传感器信息融合方法大多为"静态的",较少考虑传感器可信度变化以及测量过程中的多维特征指标权重的时效性给融合结果带来的影响.为了解决此问题,提出了一种基于模糊理论与区间型多属性决策的信息融合方法.该方法从各传感器对模糊命题支持度的一致性来定义其信息质最优化度,用区间数与多属性决策理论来定义特征识别综合置信度,并从这两方面客观确定了传感器的融合权重,较好地解决了对传感器信息与目标特征权重为模糊与不确定时的合理评价,以此构建了一个智能优化决策层融合识别模型.最后以弹道目标识别实验证明了此方法有较好的时效性和准确性. 相似文献
179.
180.