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101.
102.
影响上海市地价空间分布的区位因子分析 总被引:28,自引:5,他引:28
本文采用GIS技术和多元线性回归分析方法,以土地批租地块为样本,分析上海市地价与城市区位因子的线性关系。回归分析结果表明;南京路,市中心和淮海路是影响上海市寺价空间差异的主要区位因子,外滩,次级商业中心和交通结节点对地价的影响很小,表明上海市地价的空间分布具有很高的向心性。 相似文献
103.
静校正处理是消除近地层影响的一个重要地震资料数字处理方法,在近地表层纵,横向变化复杂,静校正量变化较大的地区,常规静校正方法和线性反演方法均不能解决问题,遗传算法是近年发展起来的一种模拟生物生化过程的较先进的非线性反演方法,对用遗传算法进行静校正的若干问题进行了讨论,说明它是可以解决表层情况复杂地区静校正问题的一个有效方法。 相似文献
104.
滑坡定量预测的非线性理论方法 总被引:19,自引:0,他引:19
滑坡时空预测是当前滑坡研究中的难题,特别是滑坡时间预测工作,其进展缓慢。本文基于非线性科学理论,分析了滑坡活动的分形特征及时间分形预测方法,研究了滑坡空间预测的人工神经网络特征,系统介绍了滑坡时间预测的非线性动力学理论。在此基础上,讨论了滑坡定量预测的发展趋势。 相似文献
105.
模拟退火剩余静校正的一步算法 总被引:1,自引:1,他引:1
当地震资料的剩余静校正量大、信噪比低时,利用传统的线性反演方法不能有效地拾取静校正量。本文介绍一种非线性反演方法(一步模拟退火法)来估算炮点和检波点的剩余静校正量。通过对合成地震记录的试算表明,该算法可获得近似于真实的剩余静校正量。 相似文献
106.
Y. -K. Tung K. -C. Yeh J. -C. Yang 《Stochastic Environmental Research and Risk Assessment (SERRA)》1997,11(2):145-171
Hydrologic regionalization is a useful tool that allows for the transfer of hydrological information from gaged sites to ungaged
sites. This study developed regional regression equations that relate the two parameters in Nash's IUH model to the basin
characteristics for 42 major watersheds in Taiwan. In the process of developing the regional equations, different regression
procedures including the conventional univariate regression, multivariate regression, and seemingly unrelated regression were
used. Multivariate regression and seeming unrelated regression were applied because there exists a rather strong correlation
between the Nash's IUH parameters. Furthermore, a validation study was conducted to examine the predictability of regional
equations derived by different regression procedures. The study indicates that hydrologic regionalization involving several
dependent variables should consider their correlations in the process of establishing the regional equations. The consideration
of such correlation will enhance the predictability of resulting regional equations as compared with the ones from the conventional
univariate regression procedure. 相似文献
107.
The separation of the influence of nutrients and climate on the varve time-series of baldeggersee, Switzerland 总被引:7,自引:2,他引:7
The varve data-set from a freeze-core taken in the deepest part of Baldeggersee was subjected to different multivariate statistical
analyses in order to estimate the amount of variance in the varve thickness measures explicable by past climate and by the
trophic state of the lake. A comparison of two different time-periods (1902 to1992 versus 1920 to 1980) revealed that the
lake restoration programme since 1982 has had a significant impact on the formation of the seasonal layers. Results of the
partitioning of the variance in the varve thickness measures showed that about two thirds of the variance are unexplained
by a climate and trophic state model and that trophic state explains 6%, whereas climate accounts for about 28% of the variance
before the effect of lake restoration had a strong impact on the varves. Among the climate parameters the amount of annual
precipitation is a strong predictor for explaining the thickness of both dark layer and total couplet thickness, whereas summer
precipitation is important for the thickness of the light layer. 相似文献
108.
K. -C. Yeh J. -C. Yang Y. -K. Tung 《Stochastic Environmental Research and Risk Assessment (SERRA)》1997,11(2):173-192
Hydrologic model parameters obtained from regional regression equations are subject to uncertainty. Consequently, hydrologic
model outputs based on the stochastic parameters are random. This paper presents a systematic analysis of uncertainty associated
with the two parameters, N and K, in Nash's IUH model from different regional regression equations. The uncertainty features
associated with N and K are further incorporated to assess the uncertainty of the resulting IUH. Numerical results indicate
that uncertainty of N and K from the regional regression equations are too significant to be ignored. 相似文献
109.
Hydrologic model parameters obtained from regional regression equations are subject to uncertainty. Consequently, hydrologic
model outputs based on the stochastic parameters are random. This paper presents a systematic analysis of uncertainty associated
with the two parameters, N and K, in Nash's IUH model from different regional regression equations. The uncertainty features
associated with N and K are further incorporated to assess the uncertainty of the resulting IUH. Numerical results indicate
that uncertainty of N and K from the regional regression equations are too significant to be ignored. 相似文献
110.