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1.
Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.  相似文献   
2.
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   
3.
形变大地测量学的进展、问题与地震预报   总被引:12,自引:7,他引:5  
简要概括了形变大地测量学的革命性进展,研讨了它的科学特色、功能和定义以及对地球科学和防灾减灾的推动。形变大地测量学有助于从根本上击破多年来制约地震预报的“瓶颈”,但也存在不少急待解决的问题。着重研讨了在21世纪前10年,形变大地测量学如何依托多年的学科积累并充分受益于人造卫星和数字化等新技术,开展创新性研究和试验以推进地震预报。为此,对当前的研究工作提出了12条科学技术途径。最后对学科名称提出了建议。  相似文献   
4.
Singh et al (2005) examined the potential of the ANN and neuro-fuzzy systems application for the prediction of dynamic constant of rockmass. However, the model proposed by them has some drawbacks according to fuzzy logic principles. This discussion will focus on the main fuzzy logic principles which authors and potential readers should take into consideration.  相似文献   
5.
Ringnet fishing began in the early 20th century and is practised worldwide, mainly to target nearshore pelagic species. The method was introduced to Kenya’s coastal waters by migrant fishers from Tanzania. However, the impacts of this fishing gear remain poorly assessed. We assessed the spatial distribution of ringnet fishing effort and its possible effects on ecosystem components, such as coral reefs, marine megafauna and marine protected areas, on the south coast of Kenya. We tracked 89 ringnet fishing trips made from December 2015 to January 2016 and used spatial multicriteria analysis to determine hotspots of possible environmental risks. The results showed that habitat type and bathymetric profile influenced the spatial distribution of ringnet fishing effort. Mixed seagrass and coral habitats had the highest concentration of the effort. Most of the habitats in the study area were moderately exposed to the impacts of the ringnet fishery. The study identifies high-risk areas that require spatial measures to minimise possible environmental risks of the gear both to habitats and to endangered sea turtles.  相似文献   
6.
本文介绍了智能潜器集成仿真系统的硬、软件结构.通过这一系统所展示的水下虚拟仿真环境能够在研究和开发智能潜器的控制体系结构、潜器载体的水动力学、信息融合和目标识别等工作中发挥巨大作用  相似文献   
7.
Despite the severity of tropical cyclone ‘Winifred’, which crossed the Great Barrier Reef on 1 February 1986, there were little long-term effects on lagoon surface sediments from reefs in its path. Short-term effects were apparent only at one particularly exposed area. These were: an increase in proportion of the coarse fraction, the establishment of sand ripples, and the destruction of the mounds produced by callianassid shrimps (normally the dominant topographic feature). Within six weeks this area was indistinguishable from a typical reef lagoon. This is probably the result of sediment reworking by callianassid shrimp, involving selective burial of the coarse fragments and transport to the surface of finer particles. Sediment turnover rates by callianassids are commensurate with change to the sediment within the relatively short period observed. The sediment fauna responded quickly to the changes in sediment type. Immediately after the cyclone the disturbed area supported a fauna typical of the coarse sediments on the shallow reef flat, as the sediment reverted to a more normal type so the fauna changed back to that typical of a reef lagoon.  相似文献   
8.
赤点石斑鱼人工配合饵料中蛋白质最适含量的研究   总被引:11,自引:1,他引:11  
本文探讨了不同蛋白质含量的配合饵料对赤点石斑鱼(Epinephelusakaara)生长的影响。通过60d度验得出:在各配合饵料组中,蛋白质含量为49.52%的试验的相对增重率(46.84%)体长相对增长率(15.96%)、蛋白质效率(60.35%)和饵料转化率(29.85%)等均为最佳。配合饵料组鱼体肌肉营养成分(蛋白质、脂肪、氨基酸和鲜味氨基酸)也均优于对照组,而更接近野生鱼。经回归方程分析,赤点石斑鱼人工配合饵料中蛋白质最适含量为48.37%~49.24%。  相似文献   
9.
地形坡度对多金属结核分布的控制作用   总被引:3,自引:3,他引:3  
选取我国东太平洋多金属结核开辟区内的一个区域作为研究区,利用人工神经网络中应用最为广泛的BP网络,建立控制多金属结核分布的地质因素与多金属结核分布之间的映射关系,探讨地形坡度对多金属结核分布的控制作用.结果表明,在经度、纬度、水深、坡度四个因素中,坡度对结核分布影响程度最大;多金属结核主要分布于坡度小于5°的地方;当坡度小于5°时,丰度与地形坡度呈正相关,品位与地形坡度呈负相关,丰度与品位呈负相关;品位与坡度似呈指数关系,坡度增大,品位降低.  相似文献   
10.
人工鱼礁工程的风险评估   总被引:1,自引:0,他引:1  
对台风暴潮影响下的嵊泗海域人工鱼礁工程做了风险评估,考虑了台风暴潮中出现的大浪和风暴潮减水对鱼礁联合作用的危害。风险评估分为危险灾害识别、失效概率计算、失效后果评估、风险准则评定和风险管理决策几个主要的步骤。在失效概率的计算中采用基于应用设计点的重点抽样法随机模拟的技术,这一随机模拟技术可以广泛的应用与海洋工程结构的风险评估当中。  相似文献   
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