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511.
A mathematical formulation of an optimization model designed to select projects for inclusion in an R&D portfolio, subject to a wide variety of constraints (e.g., capital, headcount, strategic intent, etc.), is presented. The model is similar to others that have previously appeared in the literature and is in the form of a mixed integer programming (MIP) problem known as the multidimensional knapsack problem. Exact solution of such problems is generally difficult, but can be accomplished in reasonable time using specialized algorithms. The main contribution of this paper is an examination of two important issues related to formulation of project selection models such as the one presented here. If partial funding and implementation of projects is allowed, the resulting formulation is a linear programming (LP) problem which can be solved quite easily. Several plausible assumptions about how partial funding impacts project value are presented. In general, our examples suggest that the problem might best be formulated as a nonlinear programming (NLP) problem, but that there is a need for further research to determine an appropriate expression for the value of a partially funded project. In light of that gap in the current body of knowledge and for practical reasons, the LP relaxation of this model is preferred. The LP relaxation can be implemented in a spreadsheet (even for relatively large problems) and gives reasonable results when applied to a test problem based on GM's R&D project selection process. There has been much discussion in the literature on the topic of assigning a quantitative measure of value to each project. Although many alternatives are suggested, no one way is universally accepted as the preferred way. There does seem to be general agreement that all of the proposed methods are subject to considerable uncertainty. A systematic way to examine the sensitivity of project selection decisions to variations in the measure of value is developed. It is shown that the solution for the illustrative problem is reasonably robust to rather large variations in the measure of value. We cannot, however, conclude that this would be the case in general. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 18–40, 2001  相似文献   
512.
We apply the techniques of response surface methodology (RSM) to approximate the objective function of a two‐stage stochastic linear program with recourse. In particular, the objective function is estimated, in the region of optimality, by a quadratic function of the first‐stage decision variables. The resulting response surface can provide valuable modeling insight, such as directions of minimum and maximum sensitivity to changes in the first‐stage variables. Latin hypercube (LH) sampling is applied to reduce the variance of the recourse function point estimates that are used to construct the response surface. Empirical results show the value of the LH method by comparing it with strategies based on independent random numbers, common random numbers, and the Schruben‐Margolin assignment rule. In addition, variance reduction with LH sampling can be guaranteed for an important class of two‐stage problems which includes the classical capacity expansion model. © 1999 John Wiley & Sons, Inc. Naval Research Logistics 46: 753–776, 1999  相似文献   
513.
为了尽快分析出未知水雷障碍参数,根据水雷战的特点,提出了建立未知水雷障碍参数分析专家系统的观点,对专家系统的设计方法进行了一定的探讨,并针对专家系统建立中的"瓶颈"问题,提出了基于Vague集插值近似推理的专家系统知识自动获取方法,在介绍推理过程的基础上给出了算例.从推理的结果来看,该方法具有较高的可信度,从而为专家系统的研制提供了一定的方法支持.  相似文献   
514.
We consider a design problem for wastewater treatment systems that considers uncertainty in pollutant concentration levels at water sources. The goal is to optimize the selection of treatment technologies and pipeline connections, so that treated wastewater can achieve specified effluents discharge limits as well as possible. We propose a new two-stage model to optimize a set of guarantee levels, that is, the maximum concentration level of source pollutants for which treated wastewater can be compliant with discharge limits. In the first stage, treatment technologies and pipeline connections are selected. In the second stage, when pollutant concentration levels are revealed, wastewater distribution and mixing are determined. A key attractiveness of the proposed guarantee rate optimization model is that it can be simplified into a single-stage mixed-integer linear program. In our numerical experiments based on real-world pollutants data, the guarantee rate model demonstrates its advantages in terms of computational efficiency, scalability and solution quality, compared with the standard probability maximization model. Finally, the methodology proposed in this paper can also be applied to other two-stage problems under uncertainty with similar uncertainty characteristics.  相似文献   
515.
为了提高永磁直线同步电机伺服系统的鲁棒性,提出基于自抗扰思想的反步控制器。将永磁直线同步电机伺服系统中的未建模动态和外界扰动定义为总和扰动,并扩充为系统新的状态变量。设计了线性扩张状态观测器估计不可直接测量的直线电机动子速度以及总和扰动,证明并分析了设计的线性扩张状态观测器的收敛性和估计误差。利用线性扩张状态观测器的输出,基于动态补偿线性化思想设计了反步控制器。证明了考虑线性扩张状态观测器估计误差的闭环反馈控制系统的稳定性。在Googol公司的实验平台上,验证了设计的自抗扰反步控制器的可行性。  相似文献   
516.
为了提高线式爆炸分离装置的安全性,本研究基于扩展有限元法,通过创建二维和三维动态裂纹扩展模型,探索了线式爆炸分离装置在爆轰波作用过程中的动态裂纹扩展和止裂机理。研究表明,分离壳体的裂纹扩展路径独立于裂纹初始角度;不考虑载荷时序时,二维和三维动态裂纹扩展的主方向分别沿着分离壳体的径向和环向;考虑载荷时序时,受不同区域应力波的联合作用,三维裂纹沿环向扩展的同时会沿着轴向扩展,但裂纹的扩展均不会影响到止裂槽以外的结构。所提方法和相应结论可为线式爆炸分离装置设计提供参考。  相似文献   
517.
为了解决直线电机伺服系统跟踪速度与峰化现象之间的矛盾,设计一种基于非线性扩张状态观测器的比例微分(Proportion Differentiation,PD)控制器。将直线电机伺服系统中的未建模动态和外界干扰定义为总和扰动并扩充为系统新的状态变量,利用非线性扩张状态观测器(Non Linear Extended State Observer,NLESO)估计不可测量的直线电机动子速度以及总和扰动。利用NLESO和跟踪微分器TD的输出,基于动态补偿线性化思想设计了引入补偿量的PD控制器,并给出了闭环控制系统稳定性证明。在Googol公司的实验平台上,通过与两种基于LESO的PD控制器对比,验证了所设计的基于NLESO的PD控制器的可行性。实验结果表明,基于NLESO的PD控制器可使直线电机伺服系统具有跟踪速度快、跟踪精度高、峰化现象小、鲁棒性强的优点。  相似文献   
518.
多智能体集群作战是未来战场的重要形式.作为集群作战中的关键技术,编队控制有着广泛的应用.以编队控制律为研究目标,选择2种优化控制方法:线性二次型调节器(linear quadratic regulator,LQR)方法和模型预测控制(model predictive control,MPC)方法.针对圆形编队轨迹,采用...  相似文献   
519.
双泵源电液舵机线谱噪声控制   总被引:1,自引:0,他引:1       下载免费PDF全文
采取变频调速控制策略的电液舵机可大幅降低操舵噪声,但系统线谱噪声明显且随工况变化而迁移,衰减难度大。基于此,结合泵源双冗余的电液舵机原理,仅改变原系统控制策略,提出基于辅助泵源合流的压力脉动控制措施。理论分析指出,两泵源转速一致,初始相位角为半个周期可衰减奇数次谐波。设计了主从同步控制策略,配置相应硬件,并应用于实际系统,实测相同操舵工况下可降低基脚结构振动总级3~5 dB,一阶线谱最大可衰减23 dB。  相似文献   
520.
In urban rail transit systems of large cities, the headway and following distance of successive trains have been compressed as much as possible to enhance the corridor capacity to satisfy extremely high passenger demand during peak hours. To prevent train collisions and ensure the safety of trains, a safe following distance of trains must be maintained. However, this requirement is subject to a series of complex factors, such as the uncertain train braking performance, train communication delay, and driver reaction time. In this paper, we propose a unified mathematical framework to analyze the safety‐oriented reliability of metro train timetables with different corridor capacities, that is, the train traffic density, and determine the most reliable train timetable for metro lines in an uncertain environment. By employing a space‐time network representation in the formulations, the reliability‐based train timetabling problem is formulated as a nonlinear stochastic programming model, in which we use 0‐1 variables to denote the time‐dependent velocity and position of all involved trains. Several reformulation techniques are developed to obtain an equivalent mixed integer programming model with quadratic constraints (MIQCP) that can be solved to optimality by some commercial solvers. To improve the computational efficiency of the MIQCP model, we develop a dual decomposition solution framework that decomposes the primal problem into several sets of subproblems by dualizing the coupling constraints across different samples. An exact dynamic programming combined with search space reduction strategies is also developed to solve the exact optimal solutions of these subproblems. Two sets of numerical experiments, which involve a relatively small‐scale case and a real‐world instance based on the operation data of the Beijing subway Changping Line are implemented to verify the effectiveness of the proposed approaches.  相似文献   
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