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11.
Methodology and use of tensor invariants for satellite gravity gradiometry   总被引:2,自引:1,他引:1  
Although its use is widespread in several other scientific disciplines, the theory of tensor invariants is only marginally adopted in gravity field modeling. We aim to close this gap by developing and applying the invariants approach for geopotential recovery. Gravitational tensor invariants are deduced from products of second-order derivatives of the gravitational potential. The benefit of the method presented arises from its independence of the gradiometer instrument’s orientation in space. Thus, we refrain from the classical methods for satellite gravity gradiometry analysis, i.e., in terms of individual gravity gradients, in favor of the alternative invariants approach. The invariants approach requires a tailored processing strategy. Firstly, the non-linear functionals with regard to the potential series expansion in spherical harmonics necessitates the linearization and iterative solution of the resulting least-squares problem. From the computational point of view, efficient linearization by means of perturbation theory has been adopted. It only requires the computation of reference gravity gradients. Secondly, the deduced pseudo-observations are composed of all the gravitational tensor elements, all of which require a comparable level of accuracy. Additionally, implementation of the invariants method for large data sets is a challenging task. We show the fundamentals of tensor invariants theory adapted to satellite gradiometry. With regard to the GOCE (Gravity field and steady-state Ocean Circulation Explorer) satellite gradiometry mission, we demonstrate that the iterative parameter estimation process converges within only two iterations. Additionally, for the GOCE configuration, we show the invariants approach to be insensitive to the synthesis of unobserved gravity gradients.  相似文献   
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Seismic hazard analysis is based on data and models, which both are imprecise and uncertain. Especially the interpretation of historical information into earthquake parameters, e.g. earthquake size and location, yields ambiguous and imprecise data. Models based on probability distributions have been developed in order to quantify and represent these uncertainties. Nevertheless, the majority of the procedures applied in seismic hazard assessment do not take into account these uncertainties, nor do they show the variance of the results. Therefore, a procedure based on Bayesian statistics was developed to estimate return periods for different ground motion intensities (MSK scale).Bayesian techniques provide a mathematical model to estimate the distribution of random variables in presence of uncertainties. The developed method estimates the probability distribution of the number of occurrences in a Poisson process described by the parameter . The input data are the historical occurrences of intensities for a particular site, represented by a discrete probability distribution for each earthquake. The calculation of these historical occurrences requires a careful preparation of all input parameters, i.e. a modelling of their uncertainties. The obtained results show that the variance of the recurrence rate is smaller in regions with higher seismic activity than in less active regions. It can also be demonstrated that long return periods cannot be estimated with confidence, because the time period of observation is too short. This indicates that the long return periods obtained by seismic source methods only reflects the delineated seismic sources and the chosen earthquake size distribution law.  相似文献   
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Let there be given a twodimensional symmetric rank two tensor of random type (examples:strain, stress) which is either directly observed or indirectly estimated from observations by an adjustment procedure. Under the assumption of normalityof tensor components we compute the joint probability density functionas well as the marginal probability density functionsof its eigenspectra (eigenvalues) and eigendirections (orientation parameters). Due to the nonlinearity of the relation between eigenspectra-eigendirections and the random tensor components, via the inverse nonlinear error propagationbiases and aliases of their first and centralized second moments (mean value, variance-covariance) are expressed in terms of Jacobianand Hessianmatrices. The joint probability density function and the first and second moments thus form the fundamental of hypothesis testing and qualify control of eigenspectra (eigenvalues, principal components) and eigendirections (orientation parameters, eigenvectors, principial direction) of a twodimensional, symmetric rank two random tensor.  相似文献   
14.
Laboratory Studies Of Wind Stress Over Surface Waves   总被引:4,自引:0,他引:4  
Simultaneous laboratory observations of wind speed, wind stress, and surfacewind-wave spectra are made under a variety of wind forcing patterns using cleanwater as well as water containing an artificial surfactant. Under typical experimentalconditions, more than half of the total stress is supported by the wave-induced stressrather than by the surface viscous stress. When the surfactant reduces the shortwind-wave spectra, the wind stress also decreases by as much as 20–30% at agiven wind speed. When the wind forcing is modulated in time, the wind stresstends to be higher under decreasing wind than under increasing wind at a givenwind speed, mainly because the response of short wind-wave spectra to varyingwind forcing is delayed in time. These examples clearly demonstrate that therelationship between the wind speed and the wind stress can be significantlymodified if the surface wave field is not in equilibrium with the wind forcing.Next, we examine whether the wind stress is estimated accurately if the wave-inducedstress by all surface wave components is explicitly evaluated by linear superpositionand is added to the surface viscous stress. It is assumed that the surface viscous stressis uniquely related to the wind speed, and that the wind input rate is determined by thelocal, reduced turbulent stress rather than the total stress. Our wind stress estimatesincluding the wave contributions agree well with observed wind stress values, evenif the surface wave field is away from its equilibrium with the wind in the presenceof surface films and/or under time-transient wind forcing. These observations stronglysuggest that the wind stress is accurately evaluated as a sum of the wave-induced stressand the surface viscous stress. At very high winds, our stress estimates tend to be lowerthan the observations. We suspect that this is because of the enhancement of wind stressover very steep (or breaking) short wind-waves.  相似文献   
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This paper explores the issue of climate vulnerability in Norway, an affluent country that is generally considered to be resilient to the impacts of climate change. In presenting a multi-scale assessment of climate change impacts and vulnerability in Norway, we show that the concept of vulnerability depends on the scale of analysis. Both exposure and the distribution of climate sensitive sectors vary greatly across scale. So do the underlying social and economic conditions that influence adaptive capacity. These findings question the common notion that climate change may be beneficial for Norway, and that the country can readily adapt to climate change. As scale differences are brought into consideration, vulnerability emerges within some regions, localities, and social groups. To cope with actual and potential changes in climate and climate variability, it will be necessary to acknowledge climate vulnerabilities at the regional and local levels, and to address them accordingly. This multi-scale assessment of impacts and vulnerability in Norway reinforces the importance of scale in global change research.  相似文献   
18.
This paper is concerned with numerical tests of several rock physical relationships. The focus is on effective velocities and scattering attenuation in 3D fractured media. We apply the so‐called rotated staggered finite‐difference grid (RSG) technique for numerical experiments. Using this modified grid, it is possible to simulate the propagation of elastic waves in a 3D medium containing cracks, pores or free surfaces without applying explicit boundary conditions and without averaging the elastic moduli. We simulate the propagation of plane waves through a set of randomly cracked 3D media. In these numerical experiments we vary the number and the distribution of cracks. The synthetic results are compared with several (most popular) theories predicting the effective elastic properties of fractured materials. We find that, for randomly distributed and randomly orientated non‐intersecting thin penny‐shaped dry cracks, the numerical simulations of P‐ and S‐wave velocities are in good agreement with the predictions of the self‐consistent approximation. We observe similar results for fluid‐filled cracks. The standard Gassmann equation cannot be applied to our 3D fractured media, although we have very low porosity in our models. This is explained by the absence of a connected porosity. There is only a slight difference in effective velocities between the cases of intersecting and non‐intersecting cracks. This can be clearly demonstrated up to a crack density that is close to the connectivity percolation threshold. For crack densities beyond this threshold, we observe that the differential effective‐medium (DEM) theory gives the best fit with numerical results for intersecting cracks. Additionally, it is shown that the scattering attenuation coefficient (of the mean field) predicted by the classical Hudson approach is in excellent agreement with our numerical results.  相似文献   
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For many researchers, government agencies, and emergency responders, access to the geospatial data of US electric power infrastructure is invaluable for analysis, planning, and disaster recovery. Historically, however, access to high quality geospatial energy data has been limited to few agencies because of commercial licenses restrictions, and those resources which are widely accessible have been of poor quality, particularly with respect to reliability. Recent efforts to develop a highly reliable and publicly accessible alternative to the existing datasets were met with numerous challenges – not the least of which was filling the gaps in power transmission line voltage ratings. To address the line voltage rating problem, we developed and tested a basic methodology that fuses knowledge and techniques from power systems, geography, and machine learning domains. Specifically, we identified predictors of nominal voltage that could be extracted from aerial imagery and developed a tree-based classifier to classify nominal line voltage ratings. Overall, we found that line support height, support span, and conductor spacing are the best predictors of voltage ratings, and that the classifier built with these predictors had a reliable predictive accuracy (that is, within one voltage class for four out of the five classes sampled). We applied our approach to a study area in Minnesota.  相似文献   
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