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91.
An inexact double-sided fuzzy chance-constrained programming (IDFCCP) method was developed in this study and applied to an agricultural effluent control management problem. IDFCCP was formulated through incorporating interval linear programming (ILP) into a double-sided fuzzy chance-constrained programming (DFCCP) framework, and could be used to deal with uncertainties expressed as not only possibility distributions associated with both left- and right-hand-side components of constraints but also discrete intervals in the objective function. The study results indicated that IDFCCP allowed violation of system constraints at specified confidence levels, where each confidence level consisted of two reliability scenarios. This could lead to model solutions with high system benefits under acceptable risk magnitudes. Furthermore, the introduction of ILP allowed uncertain information presented as discrete intervals to be communicated into the optimization process, such that a variety of decision alternatives can be generated by adjusting the decision-variable values within their intervals. The proposed model could help decision makers establish various production patterns with cost-effective water quality management schemes under complex uncertainties, and gain in-depth insights into the trade-offs between system economy and reliability. 相似文献
92.
Abstract Many data structures are possible for the storage of topological information for computer-based maps. The PAN graph is here suggested as an aid in the selection of a strategy appropriate to the application. Examples are given for the mapping of triangular networks and Thiessen polygons. Application of the technique is appropriate to both education in, and design of, spatial data structures for automated cartography and geographical information systems 相似文献
93.
Henry Ker–Chang Chang Chung–Yu Liou 《International journal of geographical information science》2013,27(2):205-218
ABSTRACT Although the linear quadtree is popular in both image processing and GIS, most linear quadtree coding methods need in representation a bit length that is proportional to the resolution of images; the proportionality factor is replaced with a constant bit length that induces a more compact linear quadtree. We propose a linear quadtree coding scheme named constant key length quadtree coding (CKQC) that has advantages of easy implementation and decreased memory requirements. The proposed CKQC scheme is developed on the bases of node classification, order of traversal with breadth first and the Morton sequence. The major characteristic is to apply a constant bit length to construct quaternary codes. The bit length of each quaternary code is constant, either four or eight bits, no matter what the resolution of a raster image. In terms of memory space required and duration complexities, the overall performance is analyzed and compared with other methods to demonstrate the superiority of the proposed CKQC scheme. Several experimental results validate the applicability of the proposed scheme. 相似文献
94.
J. L. Silván‐Cárdenas L. Wang F. B. Zhan 《International journal of geographical information science》2013,27(3):295-318
The degree of uncertainty of many geographical objects has long been known to be in intimate relation with the scale of its observation and representation. Yet, the explicit consideration of scaling operations when modeling uncertainty is rarely found. In this study, a neural network‐based data model was investigated for representing geographical objects with scale‐induced indeterminate boundaries. Two types of neural units, combined with two types of activation function, comprise the processing core of the model, where the activation function can model either hard or soft transition zones. The construction of complex fuzzy regions, as well as lines and points, is discussed and illustrated with examples. It is shown how the level of detail that is apparent in the boundary at a given scale can be controlled through the degree of smoothness of each activation function. Several issues about the practical implementation of the model are discussed and indications on how to perform complex overlay operations of fuzzy maps provided. The model was illustrated through an example of representing multi‐resolution, sub‐pixel maps that are typically derived from remote sensing techniques. 相似文献
95.
ALEX HAGEN-ZANKER BAS STRAATMAN INGE ULJEE 《International journal of geographical information science》2013,27(7):769-785
Fuzzy set map comparison offers a novel approach to map comparison.The approach is specifically aimed at categorical raster maps and applies fuzzy set techniques, accounting for fuzziness of location and fuzziness of category, to create a similarity map as well as an overall similarity statistic: the Fuzzy Kappa. To date, the calculation of the Fuzzy Kappa (or K-fuzzy) has not been formally derived, and the documented procedure was only valid for cases without fuzziness of category. Furthermore, it required an infinitely large, edgeless map. This paper presents the full derivation of the Fuzzy Kappa; the method is now valid for comparisons considering fuzziness of both location and category and does not require further assumptions. This theoretical completion opens opportunities for use of the technique that surpass the original intentions. In particular, the categorical similarity matrix can be applied to highlight or disregard differences pertaining to selected categories or groups of categories and to distinguish between differences due to omission and commission. 相似文献
96.
地下水资源价值的影响因素众多,价值系统具有模糊性和复杂性。建立了北京市第四系地下水资源价值评价指标体系,运用模糊数学模型对北京市地下水资源价值进行了综合评价,对合理制定水价具有一定的借鉴意义。 相似文献
97.
Wenzhong Shi Kimfung Liu Hua Zhang 《International Journal of Applied Earth Observation and Geoinformation》2011
The multiple classifier system (MCS) is an effective automatic classification method, useful in connection with remote sensing analysis techniques. Combining MSC with induced fuzzy topology enables a decomposition of image classes. This fuzzy topological MCS then provides a new and improved approach to classification. The basic classification methods discussed in this paper include maximum likelihood classification (MLC), minimum distance classification (MIND) and Mahalanobis distance classification (MAH). 相似文献
98.
Assessing the collapse susceptibility of abandoned cavities at a regional scale is associated with large uncertainties that are mainly related to the very nature of the phenomena, but also to the difficulty in collecting exhaustive information at such a scale on often “forgotten” structures. In this context, the expert's role is essential, because he is able to synthesize the information resulting from the inventory and from the commonly imprecise, if not vague, criteria on the basis of his experience and his knowledge of the geological, historical, economic regional context.In this article, we propose mathematical tools for representing and processing this information in order to give flexibility to this step and manage the uncertainty inherent in the expert's information. The first tool, based on the weight of evidence theory, is for managing the uncertainty due to the heterogeneous spatial distribution of the data, whereas the second tool, based on the fuzzy set theory, is for managing the imprecision and incompleteness of available data, which hinder the definition of the class boundaries of the quantitative decision criteria. Based on an appropriate representation of the uncertainty sources (related to the input data and to the expert diagnostic), we then propose a methodology that integrates the uncertainty in the final output of the collapse susceptibility assessment and provides a confidence indicator useful within the decision-making process. The proposed methodology is applied to the Arras territory in the North of France, where abandoned chalk pits (dating back to the Roman ages) and war saps located in the vicinity of the First World War front lines (i.e. covered trenches), raise both difficulties for urban planning. 相似文献
99.
Fuzzy logic controller (FLC) performance is greatly dependent on its inference rules. In most cases, the more rules being applied to an FLC, the accuracy of the control action is enhanced. Nevertheless, a large set of rules requires more computation time. As a result, an FLC implementation requires fast and high performance processors. This paper describes a simplified control scheme to design a fuzzy logic controller (FLC) for an underwater vehicle namely, deep submergence rescue vehicle (DSRV). The proposed method, known as the single input fuzzy logic controller (SIFLC), reduces the conventional two-input FLC (CFLC) to a single input FLC. The SIFLC offers significant reduction in rule inferences and simplifies the tuning process of control parameters. The performance of the proposed controller is validated via simulation by using the marine systems simulator (MSS) on the Matlab/Simulink® platform. During simulation, the DSRV is subjected to ocean wave disturbances. The results indicate that the SIFLC, Mamdani and Sugeno type CFLC give identical response to the same input sets. However, an SIFLC requires very minimum tuning effort and its execution time is in the orders of two magnitudes less than CFLC. 相似文献
100.
通过野外采样和室内测定,以日照茶树种植区3个典型茶园为研究对象,每个茶园分别取鸠坑、黄山群体、福鼎大白各3个品种,最终取得9种茶样生长地的土样,研究分析土样的pH,有机质,全N,P,K,有效N,P,K等指标的土壤养分含量状况,并以此为评价指标,运用模糊综合评判法,对3个茶园的土壤肥力质量进行了综合评价。结果表明,茶园肥力综合水平为北垛春>碧波山庄>北叶青;茶园土壤总体上,pH值较适中,有机质含量很缺乏,全N含量偏低,全P含量中等,全K含量较高,有效N含量很缺乏,有效P含量非常丰富,有效K含量中等,并据此提出了关于该地区3个典型茶园今后合理施肥的一些建议。 相似文献