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91.
Peter Doucette Peggy Agouris Anthony Stefanidis Mohamad Musavi 《ISPRS Journal of Photogrammetry and Remote Sensing》2001,55(5-6)
The extraction of road networks from digital imagery is a fundamental image analysis operation. Common problems encountered in automated road extraction include high sensitivity to typical scene clutter in high-resolution imagery, and inefficiency to meaningfully exploit multispectral imagery (MSI). With a ground sample distance (GSD) of less than 2 m per pixel, roads can be broadly described as elongated regions. We propose an approach of elongated region-based analysis for 2D road extraction from high-resolution imagery, which is suitable for MSI, and is insensitive to conventional edge definition. A self-organising road map (SORM) algorithm is presented, inspired from a specialised variation of Kohonen's self-organising map (SOM) neural network algorithm. A spectrally classified high-resolution image is assumed to be the input for our analysis. Our approach proceeds by performing spatial cluster analysis as a mid-level processing technique. This allows us to improve tolerance to road clutter in high-resolution images, and to minimise the effect on road extraction of common classification errors. This approach is designed in consideration of the emerging trend towards high-resolution multispectral sensors. Preliminary results demonstrate robust road extraction ability due to the non-local approach, when presented with noisy input. 相似文献
92.
Giles M. Foody 《Journal of Geographical Systems》2001,3(3):217-232
Neural networks are attractive tools for the derivation of thematic maps from remotely sensed data. Most attention has focused
on the multilayer perceptron (MLP) network but other network types are available and have different properties that may sometimes
be more appropriate for some applications. Here a MLP, radial basis function (RBF) and probabilistic neural network (PNN)
were used to classify remotely sensed data of an agricultural site. The accuracy of these classifications ranged from 86.25–91.25%.
The accuracy of the PNN classification could be increased through the incorporation of prior probabilities of class membership
but the accuracy of each classification could also be degraded by the presence of an untrained class. Post-classification
analyses, however, could be used to identify potentially misclassified cases, including those belonging to an untrained class,
to increase accuracy. The effect of the post-classification analysis on the accuracy of the classification derived from each
of the three network types investigated differed and it is suggested that network type be selected carefully to meet the requirements
of the application in-hand.
Received: 23 March 2000 / Accepted: 9 July 2000 相似文献
93.
Computer networks like the Internet are gaining importance in social and economic life. The accelerating pace of the adoption
of network technologies for business purposes is a rather recent phenomenon. Many applications are still in the early, sometimes
even experimental, phase. Nevertheless, it seems to be certain that networks will change the socioeconomic structures we know
today. This is the background for our special interest in the development of networks, in the role of spatial factors influencing
the formation of networks, and consequences of networks on spatial structures, and in the role of externalities. This paper
discusses a simple economic model – based on a microeconomic calculus – that incorporates the main factors that generate the
growth of computer networks. The paper provides analytic results about the generation of computer networks. The paper discusses
(1) under what conditions economic factors will initiate the process of network formation, (2) the relationship between individual
and social evaluation, and (3) the efficiency of a network that is generated based on economic mechanisms.
Received: 5 July 2000 / Accepted: 28 November 2000 相似文献
94.
This paper explores the application of Artificial Intelligent (AI) techniques for climate forecast. It pres ents a study on modelling the monsoon precipitation forecast by means of Artificial Neural Networks (ANNs). Using the historical data of the total amount of summer rainfall over the Delta Area of Yangtze River in China, three ANNs models have been developed to forecast the monsoon precipitation in the corre sponding area one year, five-year, and ten-year forward respectively. Performances of the models have been validated using a 'new' data set that has not been exposed to the models during the processes of model development and test. The experiment results are promising, indicating that the proposed ANNs models have good quality in terms of the accuracy, stability and generalisation ability. 相似文献
95.
文章在深入调查研究的基础上,分析了教育和科技落后、劳动者整体素质低下对陕北地区经济、社会可持续发展的不良影响。进而提出了陕北地区应当致力于人力资源培育机制创新的战略思路,即通过调整办学思路、改变办学模式等方式来促进职业技术教育和继续教育的大力发展;改革科技体制,引入竞争机制,鼓励科研人员积极开展科技推广工作和自主创业,达到科技推广、项目开发与人才培育共赢的目的。 相似文献
96.
分析了广西的基本区情条件,揭示了广西区域开发格局的空间变动趋势,提出了广西新世纪实施可持续发展战略的举措,即加强以交通为主的基础设施建设,开发以洪水河为主的水能资源,加快建设成为南中国西南东输的枢纽;调整和优化产业结构,确立主导产业的市场地位,提升优势产业的市场竞争力;加快城乡转型的进程,提高城镇化的水平和质量,控制人口增长、提高人口质量,治理环境污染;制度创新, 优化经济布局的区域结构。 相似文献
97.
应用前馈人工神经网络对广域单调的两组样本进行了模拟反演,引入单调前馈网络的概念对其权值和阈值定解问题和泛化能力进行了较诉研究。表明前馈人工神经网络是一个表达形式简单的复杂系统,其单调特征是隐性的,而且训练网络的成熟性对样本数量和样本内在规律性有一定依赖。强调了前馈人工神经网络的应用效果,指出单调与复合问题还需进一步深入研究。 相似文献
98.
An important problem in hydrologic science is understanding how river flow is influenced by rainfall properties and drainage basin characteristics. In this paper we consider one approach, the use of mass exponents, in examining the relation of river flow to rainfall and the channel network, which provides the primary conduit for transport of water to the outlet in a large basin. Mass exponents, which characterize the power-law behavior of moments as a function of scale, are ideally suited for defining scaling behavior of processes that exhibit a high degree of variability or intermittency. The main result in this paper is an expression relating the mass exponent of flow resulting from an instantaneous burst of rainfall to the mass exponents of spatial rainfall and that of the network width function. Spatial rainfall is modeled as a random multiplicative cascade and the channel network as a recursive replacement tree; these fractal models reproduce certain types of self-similar behavior seen in actual rainfall and networks. It is shown that under these modeling assumptions the scaling behavior of flow mirrors that of rainfall if rainfall is highly variable in space, and on the other hand flow mirrors the structure of the network if rainfall is not so highly variable. 相似文献
99.
100.