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981.
由于具有能以任意精度逼近任意复杂非线性函数的优良性能,神经网络在灰色系统预测中得到了较大的应用。在已有的研究基础上,针对灰色神经网络进化时容易陷入局部最优,参数修正受阻的问题,建立基于遗传粒子群混合算法优化的新型灰色神经网络模型。首先将灰色神经网络进行数学建模,以便于优化算法的应用;其次,综合遗传算法与粒子群算法的优点,构造一种混合算法,运用混合算法对灰色神经网络进行优化;最后通过日本入华游客数量预测的算例研究,比较新型灰色神经网络与灰色神经网络、单一算法优化的灰色神经网络的预测精度。所得结果表明,混合算法优化的新灰色神经网络具有更好的预测性能,在社会经济领域有着广泛的应用前景。 相似文献
982.
983.
Accurate diagnosis of a molecularly defined subtype of cancer is often an important step toward its effective control and treatment. For the diagnosis of some subtypes of a cancer, a gold standard with perfect sensitivity and specificity may be unavailable. In those scenarios, tumor subtype status is commonly measured by multiple imperfect diagnostic markers. Additionally, in many such studies, some subjects are only measured by a subset of diagnostic tests and the missing probabilities may depend on the unknown disease status. In this paper, we present statistical methods based on the EM algorithm to evaluate incomplete multiple imperfect diagnostic tests under a missing at random assumption and one missing not at random scenario. We apply the proposed methods to a real data set from the National Cancer Institute (NCI) colon cancer family registry on diagnosing microsatellite instability for hereditary non-polyposis colorectal cancer to estimate diagnostic accuracy parameters (i.e. sensitivities and specificities), prevalence, and potential differential missing probabilities for 11 biomarker tests. Simulations are also conducted to evaluate the small-sample performance of our methods. 相似文献
984.
Hanieh Panahi 《Journal of applied statistics》2014,41(1):215-232
This article deals with the statistical inference and prediction on Burr Type XII parameters based on Type II censored sample. It is observed that the maximum likelihood estimators (MLEs) cannot be obtained in closed form. We use the expectation-maximization algorithm to compute the MLEs. We also obtain the Bayes estimators under symmetric and asymmetric loss functions such as squared error and Linex By applying Lindley's approximation and Markov chain Monte Carlo (MCMC) technique. Further, MCMC samples are used to calculate the highest posterior density credible intervals. Monte Carlo simulation study and two real-life data-sets are presented to illustrate all of the methods developed here. Furthermore, we obtain a prediction of future order statistics based on the observed ordered because of its important application in different fields such as medical and engineering sciences. A numerical example carried out to illustrate the procedures obtained for prediction of future order statistics. 相似文献
985.
When functional data are not homogenous, for example, when there are multiple classes of functional curves in the dataset, traditional estimation methods may fail. In this article, we propose a new estimation procedure for the mixture of Gaussian processes, to incorporate both functional and inhomogenous properties of the data. Our method can be viewed as a natural extension of high-dimensional normal mixtures. However, the key difference is that smoothed structures are imposed for both the mean and covariance functions. The model is shown to be identifiable, and can be estimated efficiently by a combination of the ideas from expectation-maximization (EM) algorithm, kernel regression, and functional principal component analysis. Our methodology is empirically justified by Monte Carlo simulations and illustrated by an analysis of a supermarket dataset. 相似文献
986.
987.
Hanno Lefmann 《Journal of Combinatorial Optimization》2008,16(2):182-195
In this paper generalizations of Heilbronn’s triangle problem to convex hulls of j points in the unit square [0,1]2 are considered. By using results on the independence number of linear hypergraphs, for fixed integers k≥3 and any integers n≥k a deterministic o(n
6k−4) time algorithm is given, which finds distributions of n points in [0,1]2 such that, simultaneously for j=3,…,k, the areas of the convex hulls determined by any j of these n points are Ω((log n)1/(j−2)/n
(j−1)/(j−2)). 相似文献
988.
On minimum <Emphasis Type="Italic">m</Emphasis>-connected <Emphasis Type="Italic">k</Emphasis>-dominating set problem in unit disc graphs 总被引:1,自引:1,他引:0
Weiping Shang Frances Yao Pengjun Wan Xiaodong Hu 《Journal of Combinatorial Optimization》2008,16(2):99-106
Minimum m-connected k-dominating set problem is as follows: Given a graph G=(V,E) and two natural numbers m and k, find a subset S⊆V of minimal size such that every vertex in V∖S is adjacent to at least k vertices in S and the induced graph of S is m-connected. In this paper we study this problem with unit disc graphs and small m, which is motivated by the design of fault-tolerant virtual backbone for wireless sensor networks. We propose two approximation
algorithms with constant performance ratios for m≤2. We also discuss how to design approximation algorithms for the problem with arbitrarily large m.
This work was supported in part by the Research Grants Council of Hong Kong under Grant No. CityU 1165/04E, the National Natural
Science Foundation of China under Grant No. 70221001, 10531070 and 10771209. 相似文献
989.
危险品集成物流管理系统选址-选线模型研究 总被引:2,自引:0,他引:2
以路网的危险度瓶颈限制为切入点研究了一类危险品集成物流管理系统选址—选线问题,对应于路网危险度瓶颈限制引入安全费用非递减函数,并根据运输工具的安全配置等级构造该等级下的子网络,物流系统的选址—选线结果随着路网的调整而不断变化.危险品集成物流系统的管理存在多个目标,文中首先分析了成本、风险和风险公平性等优化目标,在说明了建模的假设条件后,建立了基于路网危险度瓶颈限制的危险品集成物流系统选址—选线的多目标模型,并根据模型给出了一种启发式算法,最后用一个算例对模型进行了数值演算. 相似文献
990.