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91.
在工作程度高的地区如何筛选矿致磁异常 总被引:1,自引:0,他引:1
分析了在工作程度高的地区进一步筛选矿致磁异常的可能性;提出了在工作程度高的地区筛选矿致磁异常的优先顺序建议。 相似文献
92.
93.
YANG Keming 《《地质学报》英文版》2008,82(6)
The foreland basin in West Sichuan is a tectonic unit that has undergone multi-periods tectonic movements of Indosinian-Yanshanian-Himalayan. Since late Triassic, it has been in a passive subsidence environment controlled by basin margin mountain systems and by the compression with abundant sediment sources. With the complex geologic setting, the main geologic characteristics of natural gas reservoir are listed as following:(1)Source rocks are coal-bearing mud and shale series with high to over maturity, and long and progressive hydrocarbon generation-displacement period. The key accumulation period is middle-late Yanshanian epoch.(2)There are three gas-bearing systems vertically, each of which has different reservoir mechanism, main-controlled factors and distribution law, so the exploration thoughts and techniques are also different.(3)Undergoing multi-period generation-migration-accumulation, oil and gas have encountered multi-period modification or destruction, and gas accumulation overpass multiple tectonic periods. So the trap type is complicated and dominated by combination traps. Because the main accumulation period of natural gas is early and the reservoir encountered the modification of strong Himalayan movement, there is great difference in the fullness degree of gas reservoirs and complicated gas-water relation. (4) Reservoir is tight to very tight, but reservoirs of relatively high quality developed under the super tight setting. (5) The key techniques for oil and gas exploration in west Sichuan foreland basin are the prediction of relatively favorable reservoirs, fractures and gas bearing; and the key techniques for oil and gas development are how to improve the penetration rate, reservoir protection and modification. 相似文献
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95.
The ionospheric eclipse factor method (IEFM) and its application to determining the ionospheric delay for GPS 总被引:4,自引:1,他引:3
A new method for modeling the ionospheric delay using global positioning system (GPS) data is proposed, called the ionospheric
eclipse factor method (IEFM). It is based on establishing a concept referred to as the ionospheric eclipse factor (IEF) λ
of the ionospheric pierce point (IPP) and the IEF’s influence factor (IFF) . The IEF can be used to make a relatively precise distinction between ionospheric daytime and nighttime, whereas the IFF
is advantageous for describing the IEF’s variations with day, month, season and year, associated with seasonal variations
of total electron content (TEC) of the ionosphere. By combining λ and with the local time t of IPP, the IEFM has the ability to precisely distinguish between ionospheric daytime and nighttime, as well as efficiently
combine them during different seasons or months over a year at the IPP. The IEFM-based ionospheric delay estimates are validated
by combining an absolute positioning mode with several ionospheric delay correction models or algorithms, using GPS data at
an international Global Navigation Satellite System (GNSS) service (IGS) station (WTZR). Our results indicate that the IEFM
may further improve ionospheric delay modeling using GPS data. 相似文献
96.
This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ 3). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ 3 time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ 3 data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ 3 predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ 3 time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ 3 reveal the best accuracy for LS + AR. 相似文献
97.
98.
大金山铅锌矿位于泰宁一政和北东东向铜多金属成矿带上,是该成矿带主要的矿种之一,也是闽北地区一个较有价值的矿床。矿床产于早元古代南山组上段,受燕山期北东东向构造控制,属中低温热液充填交代型矿床。 相似文献
99.
安溪县铅山铅锌矿区地质普查阶段开展了物探工作(激电中梯剖面、激电测深),发现了激电异常,结合矿区成矿地质条件,推断异常是由隐伏铅锌矿(化)引起,提出了进一步工作的建议,经钻探验证得以证实。该区激电异常是一个深部找矿的有效标志,电法工作为该普查区顺利转入详查阶段起了一定作用。 相似文献
100.