全文获取类型
收费全文 | 598篇 |
免费 | 130篇 |
国内免费 | 217篇 |
专业分类
测绘学 | 211篇 |
大气科学 | 313篇 |
地球物理 | 92篇 |
地质学 | 85篇 |
海洋学 | 96篇 |
天文学 | 13篇 |
综合类 | 71篇 |
自然地理 | 64篇 |
出版年
2024年 | 2篇 |
2023年 | 14篇 |
2022年 | 24篇 |
2021年 | 37篇 |
2020年 | 36篇 |
2019年 | 39篇 |
2018年 | 34篇 |
2017年 | 47篇 |
2016年 | 46篇 |
2015年 | 40篇 |
2014年 | 45篇 |
2013年 | 55篇 |
2012年 | 48篇 |
2011年 | 39篇 |
2010年 | 36篇 |
2009年 | 39篇 |
2008年 | 38篇 |
2007年 | 49篇 |
2006年 | 48篇 |
2005年 | 43篇 |
2004年 | 31篇 |
2003年 | 17篇 |
2002年 | 11篇 |
2001年 | 19篇 |
2000年 | 14篇 |
1999年 | 13篇 |
1998年 | 11篇 |
1997年 | 20篇 |
1996年 | 12篇 |
1995年 | 6篇 |
1994年 | 8篇 |
1993年 | 6篇 |
1992年 | 4篇 |
1991年 | 2篇 |
1990年 | 5篇 |
1989年 | 1篇 |
1988年 | 3篇 |
1987年 | 2篇 |
1986年 | 1篇 |
排序方式: 共有945条查询结果,搜索用时 15 毫秒
1.
New Earth observation missions and technologies are delivering large amounts of data. Processing this data requires developing and evaluating novel dimensionality reduction approaches to identify the most informative features for classification and regression tasks. Here we present an exhaustive evaluation of Guided Regularized Random Forest (GRRF), a feature selection method based on Random Forest. GRRF does not require fixing a priori the number of features to be selected or setting a threshold of the feature importance. Moreover, the use of regularization ensures that features selected by GRRF are non-redundant and representative. Our experiments based on various kinds of remote sensing images, show that GRRF selected features provides similar results to those obtained when using all the available features. However, the comparison between GRRF and standard random forest features shows substantial differences: in classification, the mean overall accuracy increases by almost 6% and, in regression, the decrease in RMSE almost reaches 2%. These results demonstrate the potential of GRRF for remote sensing image classification and regression. Especially in the context of increasingly large geodatabases that challenge the application of traditional methods. 相似文献
2.
3.
利用图像分形编码中定义域块和最小均方误差一一对应的特点,提出了1种基于分形编码的多姿态、表情的人脸图像检索方法。该方法将待检索图像分割为相同大小的值域块,然后将每一值域块按给定的定义域块进行分形编码,得到最小均方误差,计算该最小均方误差与图像库中最小均方误差的欧氏距离。将待检索图像所有值域块的欧氏距离求平均,此平均欧氏距离较小的几幅图像即为检索出的图像。实验证明该方法能够准确地检索出图像库中存储的同一人的不同姿态、表情的图像。 相似文献
4.
In this paper we review levels of net loss, what happens to the gear once it has been lost, and the resulting levels of ‘ghost catches’ made in passive net fisheries in the EU. We also consider ghost catches resulting from lost gear in other types of fisheries, and the extent to which the value of ghost catches has been quantified. We consider why fishing gear is lost, and profile common management responses. We present a cost benefit model to assess the relative cost effectiveness of different management measures, and suggest that gear retrieval programmes may provide less value for money than other management responses. 相似文献
5.
基于BP人工神经网络的水体遥感测深方法研究 总被引:5,自引:0,他引:5
利用Landsat7ETM+遥感图像反射率和实测水深值之间的相关性,建立了动量BP人工神经网络水深反演模型,并对长江口南港河段水深进行了反演.结果表明:具有较强非线性映射能力的动量BP神经网络模型能较好地反演出长江口南港河段的水深分布情况;由于受长江口水体高含沙量的影响,模型对小于5 m的水深值反演精度较高,而对大于10 m的水深值反演精度较低. 相似文献
6.
7.
The advent of the Virtual Observatory has begun an evolution in the space physics data environment. A number of nascent and
discipline specific Virtual Observatories have started to emerge with an emphasis on data search and retrieval. As this new
data environment takes shape an emphasis will be placed on interdisciplinary communication in attempts to address large scale
and global problems. To this end we formulate the development of a query language to facilitate Virtual Observatory to Virtual
Observatory communication. Furthermore, we outline the goals of such a language, how it would work and how existing community
efforts can be leveraged to speed the development of this query language.
相似文献
T.W. NarockEmail: |
8.
Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (Xn, n 0) or (Xt, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Yn, n 0) or (Yt, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points. 相似文献
9.
长江口水域多光谱遥感水深反演模型研究 总被引:3,自引:0,他引:3
利用Landsat-7 ETM 遥感影像反射率和实测水深值之间的相关性可以探测水深。该文介绍单波段、双波段比值和多波段3种线性回归模型以及动量BP人工神经网络水深反演模型。选择长江口北港河道上段作为研究区,利用上述模型,分两种情况进行水深反演:一是以河道全部历史样本建模;二是将河道按自然水深划分为浅水区和深水区分别建模。结果表明:神经网络模型预测精度高于线性回归模型;水深分区后线性回归和神经网络模型预测误差均有所减小。 相似文献
10.
Whereas certain linkages between stream channel morphology and stream ecology are fairly well-understood, how geomorphology influences trophic interactions remains largely unknown. As a first step, a simple, heuristic model is developed that couples reach-scale geomorphic morphology with trophic dynamics between vegetation, detritus, herbivores, and predators. Predation is assumed to increase with depth beyond a threshold depth, and herbivory is assumed to decrease with velocity beyond a threshold velocity. Results show that the modeled food chain is sensitive to channel geometry, particularly around the threshold conditions for predators and herbivores. Importantly, geomorphic influences are not isolated to a particular trophic level, but rather are transferred through the food chain via top-down and bottom-up effects. The modeled system is particularly sensitive to changes in the end-members of the food chain: vegetation and predators. Results illustrate that geomorphic disturbances, known to affect a single trophic level (e.g., fish), likely impact multiple trophic levels in the stream ecosystem via trophic interactions. Such impacts at the multiple trophic level are poorly understood. While limited by the lack of empirical long-term data for testing and calibration, this simple model provides a structure for generating hypotheses, collecting targeted data, and assessing the potential impacts of stream disturbance or restoration on entire stream ecosystems. Further, the model illustrates the potential for future coupled stream models to explore spatial and temporal linkages. 相似文献