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991.
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INTRODUCTIONAquiculturearearedtidesignalsoceanpollutionanddisaster.Althoughenvironmentscientistshaveconductedmanyin depthresearchesonthecauseandformationmechanismofredtide ,manyofitsaspectsarestillunknownbecauseredtideisacomplexphenomenonandtheecologic… 相似文献
994.
WANG Junrong LI Huajun LI Ping ZHOU Kai 《中国海洋大学学报(英文版)》2007,6(3):310-314
Coupled effects on a single point mooring(SPM) system subjected to the combined action of wind,waves and current are studied in this paper. Due to the complicatedness of the sea state and the huge size of the vessel,physical experimental study is both time consuming and uneconomical,whereas the numerical study is cost-effective and DNV software provides powerful SESAM software in solving the issues. This paper focuses on the modeling process of the SPM system,catenary equilibrium calculation,static analysis of the vessel in three different scenarios,and dynamic response simulation of the SPM system under environmental excitations. The three scenarios in study are as follows:the SPM is under the combined function of(a) wind,waves and current,(b) wind and waves,(c) current and waves. They are so set that one can compare the contributions of different types of loads in both static and dynamic studies. Numerical study shows that wind and current are the two major factors contributing to the mooring line tension,and surge and sway are the two dominant motions of the moored vessel subjected to environmental excitations. 相似文献
995.
996.
提出了一个基于3层PB神经网络的云南5月雨量的短期气候预测模型。由于神经网络本身是一个非线性动态系统,将其应用到短期气候变化预测这一非线性系统中,更能反映出气候系统状态量之间的物理关系和动力行为特性。并用该预测模型对云南5个区域1991~1998年的5月雨量距平趋势进行了共40次的预测试验和检验,其预测的距平符号相关准确率可达到77.5%。 相似文献
997.
提出了一种基于多元时间序列的Kn近邻短期气候预测模型。该模型既保留了Kn近邻算法的优良特性,同时又考虑了气候系统有关状态量之间的物理关系和动力行为特性。用该模型对云南各区域的平均月雨量距平值进行预测试验,其对云南1991年5月~1998年6月的月雨量距平值预测检验的距平符号相关准确率为63.5%,对云南1991~1998年的5月雨量距平值预测检验的距平符号相关准确率则可达到70.0%。该模型的建立具有一定的实际业务应用价值。 相似文献
998.
STUDY ON TRANSMISSION MECHANISM OF THERMAL INFRARED REMOTE SENSING FOR ABRUPT GEOTHERMAL ANOMALY IN VOLCANIC REGION 总被引:2,自引:0,他引:2
Geothermalanomalyisaphenomenonthatundergroundtemperatureandgeothermalgradientincreasesmuchmoreintheareathanitssurroundings(Xia,1979).Abruptgeothermalanomalymeansthatundergroundtemperatureonsomespotsaswellastheaffectedtemperatureofsurroundingareaabr… 相似文献
999.
Heat shocks effectively produced triploids inPenaeus chinensis. Fertilized eggs heat shocked (28–32°C) for 8 to 16 minutes, starting from 8 to 20 minutes after spawning, resulted in triploidy
induction rates of 39%–75%. Several triploid populations were cultured to 10 cm. In a triploid population, two kinds of ovaries
were observed. Histological examination showed apparent differences between these two kinds of ovaries, whereas among male
shrimp, there were no such differences.
Contribution No. 3465 from the Institute of Oceanology. Chinese Academy of Sciences.
The study was supported by the International Foundation for Science, Asian Fisheries Society and Chinese Climbing Project
PDB 6–2, and Chinese National 863 Project (No. 863-819-01-05). 相似文献
1000.
Rainfall prediction is of vital importance in water resources management. Accurate long-term rainfall prediction remains an open and challenging problem. Machine learning techniques, as an increasingly popular approach, provide an attractive alternative to traditional methods. The main objective of this study was to improve the prediction accuracy of machine learning-based methods for monthly rainfall, and to improve the understanding of the role of large-scale climatic variables and local meteorological variables in rainfall prediction. One regression model autoregressive integrated moving average model (ARIMA) and five state-of-the-art machine learning algorithms, including artificial neural networks, support vector machine, random forest (RF), gradient boosting regression, and dual-stage attention-based recurrent neural network, were implemented for monthly rainfall prediction over 25 stations in the East China region. The results showed that the ML models outperformed ARIMA model, and RF relatively outperformed other models. Local meteorological variables, humidity, and sunshine duration, were the most important predictors in improving prediction accuracy. 4-month lagged Western North Pacific Monsoon had higher importance than other large-scale climatic variables. The overall output of rainfall prediction was scalable and could be readily generalized to other regions. 相似文献