全文获取类型
收费全文 | 4273篇 |
免费 | 599篇 |
国内免费 | 588篇 |
专业分类
测绘学 | 1659篇 |
大气科学 | 444篇 |
地球物理 | 974篇 |
地质学 | 966篇 |
海洋学 | 399篇 |
天文学 | 47篇 |
综合类 | 538篇 |
自然地理 | 433篇 |
出版年
2024年 | 35篇 |
2023年 | 93篇 |
2022年 | 270篇 |
2021年 | 301篇 |
2020年 | 277篇 |
2019年 | 342篇 |
2018年 | 183篇 |
2017年 | 277篇 |
2016年 | 215篇 |
2015年 | 220篇 |
2014年 | 210篇 |
2013年 | 270篇 |
2012年 | 314篇 |
2011年 | 265篇 |
2010年 | 182篇 |
2009年 | 230篇 |
2008年 | 229篇 |
2007年 | 248篇 |
2006年 | 240篇 |
2005年 | 178篇 |
2004年 | 164篇 |
2003年 | 132篇 |
2002年 | 107篇 |
2001年 | 83篇 |
2000年 | 76篇 |
1999年 | 71篇 |
1998年 | 54篇 |
1997年 | 42篇 |
1996年 | 32篇 |
1995年 | 28篇 |
1994年 | 23篇 |
1993年 | 16篇 |
1992年 | 14篇 |
1991年 | 6篇 |
1990年 | 6篇 |
1989年 | 6篇 |
1988年 | 4篇 |
1987年 | 2篇 |
1986年 | 3篇 |
1985年 | 3篇 |
1984年 | 1篇 |
1982年 | 1篇 |
1981年 | 1篇 |
1980年 | 1篇 |
1979年 | 1篇 |
1977年 | 1篇 |
1976年 | 1篇 |
1954年 | 2篇 |
排序方式: 共有5460条查询结果,搜索用时 562 毫秒
31.
变形分析的神经网络技术应用实例 总被引:1,自引:0,他引:1
大型工程施工过程中的变形监测、分析与预报极为重要。变形分析建模的方法很多,神经网络技术的应用是其中之一。文中结合某深基坑工程的监测资料和工作经验,运用神经网络BP算法进行预测分析。简述BP神经网络的基本概念,介绍基坑变形分析的BP神经网络的具体模型结构,将神经网络方法预报结果与实测数据对比效果较好。该成果对生产实践具有参考价值。 相似文献
32.
线性最小二乘估计在对非线性函数进行线性近似的过程中会产生模型误差,而一些非线性参数估计方法可能因为函数复杂而难以求导,法方程系数矩阵秩亏或呈病态矩阵时难以求解,非线性迭代解法有时对初始值的选择存在依赖性,不恰当的初始值会导致迭代无法收敛。针对这些问题,引入了模拟退火算法,介绍了该算法的基本原理、计算步骤和收敛性,并以3个控制网平差应用为例,说明该算法具有无需求导求逆,简洁实用,易于编程等优势,并能实现全局优化,获得高精度的平差结果。 相似文献
33.
针对大样本集的训练问题和动态训练样本的模型更新问题,提出了动态最小二乘支持向量机学习算法.该算法充分利用已建好的模型,逐渐加入新样本,并可删除位于任何位置的非支持向量,避免了矩阵求逆运算,保证了算法的高效率.大坝变形及电离层延迟两个时间序列的预报实例表明,该算法具有计算时间短、预报精度高的特点. 相似文献
34.
A multi-lithology diffusive stratigraphic model is considered, which simulates at large scales in space and time the infill
of sedimentary basins governed by the interaction between tectonics displacements, eustatic variations, sediment supply, and
sediment transport laws. The model accounts for the mass conservation of each sediment lithology resulting in a mixed parabolic,
hyperbolic system of partial differential equations (PDEs) for the lithology concentrations and the sediment thickness. It
also takes into account a limit on the rock alteration velocity modeled as a unilaterality constraint. To obtain a robust,
fast, and accurate simulation, fully and semi-implicit finite volume discre tization schemes are derived for which the existence
of stable solutions is proved. Then, the set of nonlinear equations is solved using a Newton algorithm adapted to the unilaterality
constraint, and preconditioning strategies are defined for the solution of the linear system at each Newton iteration. They
are based on an algebraic approximate decoupling of the sediment thickness and the concentration variables as well as on a
proper preconditioning of each variable. These algorithms are studied and compared in terms of robustness, scalability, and
efficiency on two real basin test cases. 相似文献
35.
基于ICCP算法的重力辅助惯性导航 总被引:7,自引:0,他引:7
迭代最近等值线算法(ICCP)是一种重要的匹配导航算法,文中首先介绍ICCP算法的基本原理,随后在0.2′×0.2′重力异常数据库的基础上,利用ICCP算法进行仿真计算得到最佳匹配位置。最后为了验证匹配位置是否可用于修正惯导误差,提出将匹配位置误差作为观测量,用卡尔曼滤波对惯导系统误差进行最优估计。由最后的仿真结果可以看出,ICCP算法可有效抑制惯导纬度误差的增长,且最大纬度误差不超过2,′以匹配位置误差作为观测量可以用来估计惯导方位误差角。 相似文献
36.
37.
38.
L. I. Kuncheva J. J. Charles N. Miles A. Collins B. Wells I. S. Lim 《Mathematical Geosciences》2008,40(6):639-652
We develop the classification part of a system that analyses transmitted light microscope images of dispersed kerogen preparation. The system automatically extracts kerogen pieces from the image and labels each piece as either inertinite or vitrinite. The image pre-processing analysis consists of background removal, identification of kerogen material, object segmentation, object extraction (individual images of pieces of kerogen) and feature calculation for each object. An expert palynologist was asked to label the objects into categories inertinite and vitrinite, which provided the ground truth for the classification experiment. Ten state-of-the-art classifiers and classifier ensembles were compared: Naïve Bayes, decision tree, nearest neighbour, the logistic classifier, multilayered perceptron (MLP), support vector machines (SVM), AdaBoost, Bagging, LogitBoost and Random Forest. The logistic classifier was singled out as the most accurate classifier, with an accuracy greater than 90. Using a 10 times 10-fold cross-validation provided within the Weka software, we found that the logistic classifier was significantly better than five classifiers (p<0.05) and indistinguishable from the other four classifiers. The initial set of 32 features was subsequently reduced to 6 features without compromising the classification accuracy. A further evaluation of the system alerted us to the possible sensitivity of the classification to the ground truth that might vary from one human expert to another. The analysis also revealed that the logistic classifier made most of the correct classifications with a high certainty. 相似文献
39.
Hitoshi Oda 《Pure and Applied Geophysics》1996,147(4):719-727
By applying the perturbation theory to theXYZ algorithm (a kind of variational method), the difference f in free vibration frequencies between sphere and ellipsoid was approximated as
, where i and
i
(i = x,y andz) (i=x, y andz) are aspherical coefficients and asphericities of the ellipsoid, respectively. We developed an analytic method to compute the aspherical coefficients719-4 by using theXYZ algorithm. A numerical example was given for an ellipsoidal olivine, and an attempt was made to estimate the asphericities of the specimen by a least-squares method, based on the relationship between frequency shift and asphericity. 相似文献
40.
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