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1.
Decentralized control of vehicle formations   总被引:13,自引:3,他引:10  
This paper investigates a method for decentralized stabilization of vehicle formations using techniques from algebraic graph theory. The vehicles exchange information according to a pre-specified communication digraph, G. A feedback control is designed using relative information between a vehicle and its in-neighbors in G. We prove that a necessary and sufficient condition for an appropriate decentralized linear stabilizing feedback to exist is that G has a rooted directed spanning tree. We show the direct relationship between the rate of convergence to formation and the eigenvalues of the (directed) Laplacian of G. Various special situations are discussed, including symmetric communication graphs and formations with leaders. Several numerical simulations are used to illustrate the results.  相似文献
2.
The increasing prominence of information arising from a wide range of sources delivered over electronic media has made traditional information retrieval systems less effective. Indeed, users are overwhelmed by the information delivered by such systems in response to their queries, particularly when the latter are ambiguous. In order to tackle this problem, the state-of-the-art reveals that there is a growing interest towards contextual information retrieval which relies on various sources of evidence issued from the user’s search background and environment like interests, preferences, time and location, in order to improve the retrieval accuracy. Contextual information retrieval systems are based on different definitions of the core concept of user’s context, various user’s context modeling approaches and several techniques of document relevance measurement, but all share the goal of providing the most useful information to the users in accordance with their context. However, the evaluation methodologies conceived in the past several years for traditional information retrieval and widely used in the evaluation campaigns have been challenged by the consideration of user’s context in the information retrieval process. Thus, we recognize that a critical review of existing evaluation methodologies in contextual information retrieval area is needed in order to design and develop standard evaluation frameworks. We present in this paper a comprehensive survey of contextual information retrieval evaluation methodologies and provide insights into how and why they are appropriate to measure the retrieval effectiveness. We also highlight some of the research challenges ahead that would constitute substantive research area for future research.  相似文献
3.
面向源代码的软件模型检测及其实现   总被引:3,自引:1,他引:2       下载免费PDF全文
模型检测应用于检测软件可靠性具有重要意义.介绍了一种基于谓词抽象和反例引导抽象求精技术对源程序进行建模和验证的模型检测方法,并结合自行研发的Jchecker工具详细介绍了该软件模型检测技术的运作过程和关键算法.  相似文献
4.
5.
Remote sensing has considerable potential for providing accurate, up-to-date information in urban areas. Urban remote sensing is complicated, however, by very high spectral and spatial complexity. In this paper, Multiple Endmember Spectral Mixture Analysis (MESMA) was applied to map urban land cover using HyMap data acquired over the city of Bonn, Germany. MESMA is well suited for urban environments because it allows the number and types of endmembers to vary on a per-pixel basis, which allows controlling the large spectral variability in these environments. We employed a hierarchical approach, in which MESMA was applied to map four levels of complexity ranging from the simplest level consisting of only two classes, impervious and pervious, to 20 classes that differentiated material composition and plant species. Lower levels of complexity, mapped at the highest accuracies, were used to constrain spatially models at higher levels of complexity, reducing spectral confusion between materials. A spectral library containing 1521 endmembers was created from the HyMap data. Three endmember selection procedures, Endmember Average RMS (EAR), Minimum Average Spectral Angle (MASA) and Count Based Endmember Selection (COB), were used to identify the most representative endmembers for each level of complexity. Combined two-, three- or four-endmember models - depending on the hierarchical level - were applied, and the highest endmember fractions were used to assign a land cover class. Classification accuracies of 97.2% were achieved for the two lowest complexity levels, consisting of impervious and pervious classes, and a four class map consisting of vegetation, bare soil, water and built-up. At the next level of complexity, consisting of seven classes including trees, grass, bare soil, river, lakes/basins, road and roof/building, classification accuracies remained high at 81.7% with most classes mapped above 85% accuracy. At the highest level, consisting of 20 land cover classes, a 75.9% classification accuracy was achieved. The ability of MESMA to incorporate within-class spectral variability, combined with a hierarchical approach that uses spatial information from one level to constrain model selection at a higher level of complexity was shown to be particularly well suited for urban environments.  相似文献
6.
A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, we developed models relating field-measured response variables to plot attributes serving as the predictor variables. The plot attributes came from intersecting plot coordinates with geospatial datasets. Consequently, these models serve as mapping models. The geospatial predictor variables included Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; land cover proportions and other data from the National Land Cover Dataset (NLCD); topographic variables; monthly and annual climate parameters; and other ancillary variables. We segmented the mapping models for the U.S. into 65 ecologically similar mapping zones, plus Alaska and Puerto Rico. First, we developed a forest mask by modeling the forest vs. nonforest assignment of field plots as functions of the predictor layers using classification trees in See5©. Secondly, forest biomass models were built within the predicted forest areas using tree-based algorithms in Cubist©. To validate the models, we compared field-measured with model-predicted forest/nonforest classification and biomass from an independent test set, randomly selected from available plot data for each mapping zone. The estimated proportion of correctly classified pixels for the forest mask ranged from 0.79 in Puerto Rico to 0.94 in Alaska. For biomass, model correlation coefficients ranged from a high of 0.73 in the Pacific Northwest, to a low of 0.31 in the Southern region. There was a tendency in all regions for these models to over-predict areas of small biomass and under-predict areas of large biomass, not capturing the full range in variability. Map-based estimates of forest area and forest biomass compared well with traditional plot-based estimates for individual states and for four scales of spatial aggregation. Variable importance analyses revealed that MODIS-derived information could contribute more predictive power than other classes of information when used in isolation. However, the true contribution of each variable is confounded by high correlations. Consequently, excluding any one class of variables resulted in only small effects on overall map accuracy. An estimate of total C pools in live forest biomass of U.S. forests, derived from the nationwide biomass map, also compared well with previously published estimates.  相似文献
7.
Machine translation evaluation versus quality estimation   总被引:2,自引:2,他引:0  
Most evaluation metrics for machine translation (MT) require reference translations for each sentence in order to produce a score reflecting certain aspects of its quality. The de facto metrics, BLEU and NIST, are known to have good correlation with human evaluation at the corpus level, but this is not the case at the segment level. As an attempt to overcome these two limitations, we address the problem of evaluating the quality of MT as a prediction task, where reference-independent features are extracted from the input sentences and their translation, and a quality score is obtained based on models produced from training data. We show that this approach yields better correlation with human evaluation as compared to commonly used metrics, even with models trained on different MT systems, language-pairs and text domains.  相似文献
8.
On the cusp of a validation wall   总被引:1,自引:0,他引:1  
Traditionally, universities teach how to make or build things but not so much how to "break" things or find, patch, or prevent breaks. However, much of industry validation hinges on the latter skills. Validation is something that does not get noticed when done well, but everyone notices when something goes wrong - such as the infamous Pentium floating-point division bug. Major semiconductor companies experience postsilicon validation turning into a very expensive, time-consuming proposition, yet very few college graduates are formally trained in the area. Validation is the activity of ensuring a product satisfies its reference specifications, runs with relevant software and hardware, and meets user expectations. Here, I discuss some of the key challenges to successful validation and show why a radical transformation is necessary if validation is to be effective in the near future.  相似文献
9.
Training multilayer neural networks is typically carried out using descent techniques such as the gradient-based backpropagation (BP) of error or the quasi-Newton approaches including the Levenberg-Marquardt algorithm. This is basically due to the fact that there are no analytical methods to find the optimal weights, so iterative local or global optimization techniques are necessary. The success of iterative optimization procedures is strictly dependent on the initial conditions, therefore, in this paper, we devise a principled novel method of backpropagating the desired response through the layers of a multilayer perceptron (MLP), which enables us to accurately initialize these neural networks in the minimum mean-square-error sense, using the analytic linear least squares solution. The generated solution can be used as an initial condition to standard iterative optimization algorithms. However, simulations demonstrate that in most cases, the performance achieved through the proposed initialization scheme leaves little room for further improvement in the mean-square-error (MSE) over the training set. In addition, the performance of the network optimized with the proposed approach also generalizes well to testing data. A rigorous derivation of the initialization algorithm is presented and its high performance is verified with a number of benchmark training problems including chaotic time-series prediction, classification, and nonlinear system identification with MLPs.  相似文献
10.
Comparing spectral color computation methods   总被引:1,自引:0,他引:1  
A comparison of several schemes for spectral sampling, computation and the resultant color display reveals the relevant considerations in selecting a color computation space  相似文献
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