全文获取类型
收费全文 | 7364篇 |
免费 | 670篇 |
国内免费 | 705篇 |
专业分类
测绘学 | 2148篇 |
大气科学 | 592篇 |
地球物理 | 1741篇 |
地质学 | 1601篇 |
海洋学 | 594篇 |
天文学 | 61篇 |
综合类 | 689篇 |
自然地理 | 1313篇 |
出版年
2024年 | 48篇 |
2023年 | 140篇 |
2022年 | 345篇 |
2021年 | 412篇 |
2020年 | 366篇 |
2019年 | 378篇 |
2018年 | 207篇 |
2017年 | 297篇 |
2016年 | 287篇 |
2015年 | 291篇 |
2014年 | 325篇 |
2013年 | 461篇 |
2012年 | 412篇 |
2011年 | 387篇 |
2010年 | 302篇 |
2009年 | 384篇 |
2008年 | 404篇 |
2007年 | 479篇 |
2006年 | 408篇 |
2005年 | 335篇 |
2004年 | 317篇 |
2003年 | 291篇 |
2002年 | 243篇 |
2001年 | 235篇 |
2000年 | 172篇 |
1999年 | 143篇 |
1998年 | 160篇 |
1997年 | 108篇 |
1996年 | 78篇 |
1995年 | 81篇 |
1994年 | 78篇 |
1993年 | 49篇 |
1992年 | 31篇 |
1991年 | 15篇 |
1990年 | 19篇 |
1989年 | 14篇 |
1988年 | 17篇 |
1987年 | 8篇 |
1986年 | 4篇 |
1985年 | 2篇 |
1984年 | 4篇 |
1977年 | 2篇 |
排序方式: 共有8739条查询结果,搜索用时 15 毫秒
1.
The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
2.
Advanced material constitutive models are used to describe complex soil behaviour. These models are often used in the solution of boundary value problems under general loading conditions. Users and developers of constitutive models need to methodically investigate the represented soil response under a wide range of loading conditions. This paper presents a systematic procedure for probing constitutive models. A general incremental strain probe, 6D hyperspherical strain probe (HSP), is introduced to examine rate‐independent model response under all possible strain loading conditions. Two special cases of HSP, the true triaxial strain probe (TTSP) and the plane‐strain strain probe (PSSP), are used to generate 3‐D objects that represent model stress response to probing. The TTSP, PSSP and general HSP procedures are demonstrated using elasto‐plastic models. The objects resulting from the probing procedure readily highlight important model characteristics including anisotropy, yielding, hardening, softening and failure. The PSSP procedure is applied to a Neural Network (NN) based constitutive model. It shows that this probing is especially useful in understanding NN constitutive models, which do not contain explicit functions for yield surface, hardening, or anisotropy. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
3.
In urban environments, one major concern with deep excavations in soft clay is the potentially large ground deformations in and around the excavation. Excessive movements can damage adjacent buildings and utilities. There are many uncertainties associated with the calculation of the ultimate or serviceability performance of a braced excavation system. These include the variabilities of the loadings, geotechnical soil properties, and engineering and geometrical properties of the wall. A risk‐based approach to serviceability performance failure is necessary to incorporate systematically the uncertainties associated with the various design parameters. This paper demonstrates the use of an integrated neural network–reliability method to assess the risk of serviceability failure through the calculation of the reliability index. By first performing a series of parametric studies using the finite element method and then approximating the non‐linear limit state surface (the boundary separating the safe and ‘failure’ domains) through a neural network model, the reliability index can be determined with the aid of a spreadsheet. Two illustrative examples are presented to show how the serviceability performance for braced excavation problems can be assessed using the reliability index. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
4.
LabVIEW设计中压力传感器的RBF神经网络温度补偿 总被引:5,自引:0,他引:5
在石油平台注水压力监测系统设计中 ,采用LabVIEW虚拟仪器平台 ,嵌入逼近能力强和收敛速度快的RBF神经网络 ,以人工环境实验数据为样本进行训练 ,实现了压力传感器的智能网络温度补偿。结果显示 ,此方法能够在压力、温度变化较大的恶劣环境下 ,获得很高的补偿精度。 相似文献
5.
6.
目的:基于网络药理学与分子对接技术分析补阳还五汤治疗颈椎病的作用机制。方法:使用TCMSP、化学专业数据库获取补阳还五汤的活性成分,并对潜在靶点进行预测及规范。分别从PharmGKB、DisGeNET、OMIM、GeneCards数据库中得到颈椎病疾病靶点,利用韦恩图获取补阳还五汤与颈椎病的交集靶点。通过CytoScape软件构建中药-活性成分-疾病靶点和蛋白质-蛋白质相互作用(PPI)网络,获得核心有效成分与关键靶点,利用David数据库对潜在靶点进行富集分析。最后运用AutoDock Vina软件对补阳还五汤核心有效成分与关键靶点进行分子对接验证。结果:共获得补阳还五汤治疗颈椎病的有效活性成分97个,包括槲皮素、山柰酚、黄芩素、木犀草素等;交集靶点64个,关键靶点有白细胞介素-6(IL-6)、肿瘤坏死因子(TNF)、丝氨酸/苏氨酸蛋白激酶1(AKT1)、白细胞介素-1B(IL-1B)等;主要涉及肿瘤坏死因子(TNF)、白细胞介素-17(IL-17)、磷脂酰肌醇3-激酶(PI3K)/蛋白激酶B(Akt)等信号通路,分子对接结果显示核心有效成分与关键靶点之间结合紧密,为补阳还五汤治疗颈椎病提供相应条件。结论:该研究在总体上预测了补阳还五汤治疗颈椎病的活性成分、靶点和信号通路,作用途径广泛,为下一步的临床应用提供参考及思路。 相似文献
7.
8.
支持向量机(SVM)是近年来发展起来的机器学习的新方法,它较好地解决小样本、非线性、高维数、局部极小点等实际问题.文中研究支持向量机的拓展算法--最小二乘支持向量机(LSSVM),并将其应用于确定大面积复杂似大地水准面.通过工程实例并与神经网络模型和二次曲面多项式拟合模型相比较,验证确定区域似大地水准面的LSSVM方法的有效性. 相似文献
9.
10.
Artificial neural network and liquefaction susceptibility assessment: a case study using the 2001 Bhuj earthquake data,Gujarat, India 总被引:2,自引:0,他引:2
D. Ramakrishnan T. N. Singh N. Purwar K. S. Barde Akshay. Gulati S. Gupta 《Computational Geosciences》2008,12(4):491-501
This study pertains to prediction of liquefaction susceptibility of unconsolidated sediments using artificial neural network
(ANN) as a prediction model. The backpropagation neural network was trained, tested, and validated with 23 datasets comprising
parameters such as cyclic resistance ratio (CRR), cyclic stress ratio (CSR), liquefaction severity index (LSI), and liquefaction
sensitivity index (LSeI). The network was also trained to predict the CRR values from LSI, LSeI, and CSR values. The predicted
results were comparable with the field data on CRR and liquefaction severity. Thus, this study indicates the potentiality
of the ANN technique in mapping the liquefaction susceptibility of the area. 相似文献