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171.
We examine the problem of adaptively scheduling perfect observations and preventive replacements for a multi‐state, Markovian deterioration system with silent failures such that total expected discounted cost is minimized. We model this problem as a partially observed Markov decision process and show that the structural properties of the optimal policy hold for certain non‐extreme sample paths. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007 相似文献
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In this article, we develop a stochastic approximation algorithm to find good bid price policies for the joint capacity allocation and overbooking problem over an airline network. Our approach is based on visualizing the total expected profit as a function of the bid prices and searching for a good set of bid prices by using the stochastic gradients of the total expected profit function. We show that the total expected profit function that we use is differentiable with respect to the bid prices and derive a simple expression that can be used to compute its stochastic gradients. We show that the iterates of our stochastic approximation algorithm converge to a stationary point of the total expected profit function with probability 1. Our computational experiments indicate that the bid prices computed by our approach perform significantly better than those computed by standard benchmark strategies and the performance of our approach is relatively insensitive to the frequency with which we recompute the bid prices over the planning horizon. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011 相似文献
176.
In this article, we study reliability properties of m‐consecutive‐k‐out‐of‐n: F systems with exchangeable components. We deduce exact formulae and recurrence relations for the signature of the system. Closed form expressions for the survival function and the lifetime distribution as a mixture of the distribution of order statistics are established as well. These representations facilitate the computation of several reliability characteristics of the system for a given exchangeable joint distribution or survival function. Finally, we provide signature‐based stochastic ordering results for the system's lifetime and investigate the IFR preservation property under the formulation of m‐consecutive‐k‐out‐of‐n: F systems. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011 相似文献
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We discuss suitable conditions such that the lifetime of a series or of a parallel system formed by two components having nonindependent lifetimes may be stochastically improved by replacing the lifetimes of each of the components by an independent mixture of the individual components' lifetimes. We also characterize the classes of bivariate distributions where this phenomenon arises through a new weak dependence notion. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011 相似文献
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The Annealing Adaptive Search (AAS) algorithm for global optimization searches the solution space by sampling from a sequence of Boltzmann distributions. For a class of optimization problems, it has been shown that the complexity of AAS increases at most linearly in the problem dimension. However, despite its desirable property, sampling from a Boltzmann distribution at each iteration of the algorithm remains a practical challenge. Prior work to address this issue has focused on embedding Markov chain‐based sampling techniques within the AAS framework. In this article, based on ideas from the recent Cross‐Entropy method and Model Reference Adaptive Search, we propose an algorithm, called Model‐based Annealing Random Search (MARS), that complements prior work by sampling solutions from a sequence of surrogate distributions that iteratively approximate the target Boltzmann distributions. We establish a novel connection between MARS and the well‐known Stochastic Approximation method. By exploiting this connection, we prove the global convergence of MARS and characterize its asymptotic convergence rate behavior. Our empirical results indicate promising performance of the algorithm in comparison with some of the existing methods. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011 相似文献
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为提高智能视频监控系统中运动目标检测算法在低信噪比条件下的鲁棒性,结合混合高斯背景建模算法和随机共振原理实现一种低信噪比下的运动目标检测算法。算法根据混合高斯背景模型对当前帧生成目标概率灰度图,在本文定义的性能评价函数下,通过向该概率灰度图添加噪声使得评价函数最优化从而达到随机共振,对该随机共振灰度图进行阈值分割得到输出的检测目标。针对昏暗、大雾和红外视频分别进行了实验,证实了本文算法的有效性同时也显示本文算法相对于普通背景差算法性能获得了明显提升。 相似文献