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1.
基于折衷规划的液体动压滑动轴承多目标优化设计   总被引:1,自引:0,他引:1  
对于液体动压滑动轴承的多目标设计问题,提出了一种基于折衷规划的多目标优化方法。该方法能够对多个相互矛盾的目标函数进行折衷优化,从而达到全局最优。实例结果表明该方法能够获得比常规设计更佳的设计参数。  相似文献   
2.
一种多目标优化重建方法在气体浓度层析成像中的应用   总被引:1,自引:0,他引:1  
为了克服传统的少射线图像重建方法-ART对噪声敏感而导致的重建图像质量差的问题,在考虑气体扩散时其浓度二维分布特点的基础上,提出了一种利用多目标优化的方法来重建气体二维浓度分布图的方法.实验表明,该算法对改善气体浓度层析成像中的噪声对重建结果的影响具有较好的效果.  相似文献   
3.
For multiple-objective optimization problems, a common solution methodology is to determine a Pareto optimal set. Unfortunately, these sets are often large and can become difficult to comprehend and consider. Two methods are presented as practical approaches to reduce the size of the Pareto optimal set for multiple-objective system reliability design problems. The first method is a pseudo-ranking scheme that helps the decision maker select solutions that reflect his/her objective function priorities. In the second approach, we used data mining clustering techniques to group the data by using the k-means algorithm to find clusters of similar solutions. This provides the decision maker with just k general solutions to choose from. With this second method, from the clustered Pareto optimal set, we attempted to find solutions which are likely to be more relevant to the decision maker. These are solutions where a small improvement in one objective would lead to a large deterioration in at least one other objective. To demonstrate how these methods work, the well-known redundancy allocation problem was solved as a multiple objective problem by using the NSGA genetic algorithm to initially find the Pareto optimal solutions, and then, the two proposed methods are applied to prune the Pareto set.  相似文献   
4.
This paper presents a technique of multi-objective optimization for Model Predictive Control (MPC) where the optimization has three levels of the objective function, in order of priority: handling constraints, maximizing economics, and maintaining control. The greatest weights are assigned dynamically to control or constraint variables that are predicted to be out of their limits. The weights assigned for economics have to out-weigh those assigned for control objectives. Control variables (CV) can be controlled at fixed targets or within one- or two-sided ranges around the targets. Manipulated Variables (MV) can have assigned targets too, which may be predefined values or current actual values. This MV functionality is extremely useful when economic objectives are not defined for some or all the MVs. To achieve this complex operation, handle process outputs predicted to go out of limits, and have a guaranteed solution for any condition, the technique makes use of the priority structure, penalties on slack variables, and redefinition of the constraint and control model. An engineering implementation of this approach is shown in the MPC embedded in an industrial control system. The optimization and control of a distillation column, the standard Shell heavy oil fractionator (HOF) problem, is adequately achieved with this MPC.  相似文献   
5.
考虑土-结构动力相互作用的框架结构的参数识别研究   总被引:5,自引:0,他引:5  
对一座采用柱下独立基础的钢筋混凝土4层框架结构进行了随着层数增加的4种工况模态实验,用脉冲锤击法测试得到了各种工况的整体模态频率和振型。考虑地基-基础-上部结构动力相互作用,上部框架结构采用缩聚得到的弯剪结构模型,下部基础利用Pais等人提出的弹性地基上埋置矩形板的地基阻抗函数进行简化处理得到的计算模型。在满足地基动剪模量和各层混凝土的弹性模量随框架层数的增加而增加的原则下,建立了4种工况下的多目标优化准则。将基于频率数据识别欠定问题的灵敏度方法进行了结构物理参数以及地基参数同时识别,识别得到的模态实验值与测试值符合良好。识别结果能够反应地基基础对结构的影响并为进一步损伤诊断提供了依据。  相似文献   
6.
水库汛限水位确定方法评述与展望   总被引:15,自引:4,他引:11  
李玮  郭生练  刘攀 《水力发电》2005,31(1):66-70
回顾国内外水库防洪调度的发展概况,分析并将国内水库汛期防洪限制水位确定方法划分为汛限水位静态控制和动态控制两类。前者包括固定汛限水位法及三种分期汛限水位法;后者按照所采用的信息类别及利用的理论,划分为综合信息推理法、水文信息统计法及水库调度模型法。针对各方法给出研究及运用中的实例并做出简要分析,指出在运用中的特点。从系统的角度分析影响汛限水位确定的因素,并给出了展望。  相似文献   
7.
基于遗传退火算法的装配线设计多目标优化方法   总被引:3,自引:0,他引:3  
针对混装配线设计这一有约束的多目标优化问题,建立了数学模型。将基于Pareto的解的分级方法与Lp-范数形式的非线性机制相组合,构建了基于遗传退火算法多目标优化方法。重点阐述了个体编码、染色体检修、多目标处理机制等关键技术。设计了算法流程图,并开发了优化程序。该方法克服了加权和方法的不足,用模拟退火改善了遗传算法全局寻优性能。计算实例表明,随着迭代次数的增加,每代的非受控点逐渐收敛于Pareto最优边界,是一种混装线设计多目标优化的新方法。  相似文献   
8.
There is an ever increasing need to use optimization methods for thermal design of data centers and the hardware populating them. Airflow simulations of cabinets and data centers are computationally intensive and this problem is exacerbated when the simulation model is integrated with a design optimization method. Generally speaking, thermal design of data center hardware can be posed as a constrained multi-objective optimization problem. A popular approach for solving this kind of problem is to use Multi-Objective Genetic Algorithms (MOGAs). However, the large number of simulation evaluations needed for MOGAs has been preventing their applications to realistic engineering design problems. In this paper, details of a substantially more efficient MOGA are formulated and demonstrated through a thermal analysis simulation model of a data center cabinet. First, a reduced-order model of the cabinet problem is constructed using the Proper Orthogonal Decomposition (POD). The POD model is then used to form the objective and constraint functions of an optimization model. Next, this optimization model is integrated with the new MOGA. The new MOGA uses a “kriging” guided operation in addition to conventional genetic algorithm operations to search the design space for global optimal design solutions. This approach for optimal design is essential to handle complex multi-objective situations, where the optimal solutions may be non-obvious from simple analyses or intuition. It is shown that in optimizing the data center cabinet problem, the new MOGA outperforms a conventional MOGA by estimating the Pareto front using 50% fewer simulation calls, which makes its use very promising for complex thermal design problems. Recommended by: Monem Beitelmal  相似文献   
9.
The paper deals with the identification of Pareto optimal solutions using GA based coevolution in the context of multiobjective optimization. Coevolution is a genetic process by which several species work with different types of individuals in parallel. The concept of cooperative coevolution is adopted to compensate for each of single objective optimal solutions during genetic evolution. The present study explores the GA based coevolution, and develops prescribed and adaptive scheduling schemes to reflect design characteristics among single objective optimization. In the paper, non-dominated Pareto optimal solutions are obtained by controlling scheduling schemes and comparing each of single objective optimal solutions. The proposed strategies are subsequently applied to a three-bar planar truss design and an energy preserving flywheel design to support proposed strategies.  相似文献   
10.
Generally,the process of designing missile con-trol systeminvolves a great deal manual modificationsand trials in order to meet all the design specifica-tions ,such as robust stability, noise rejection, dy-namic response , steady tracking error , etc . So thedesignis an opti mization problemin nature . Becausegenetic algorithm(GA) is a search algorithmbased onthe mechanismof natural selection and natural genet-ics and is different from conventional opti mization.GAsearches for a population of…  相似文献   
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