共查询到19条相似文献,搜索用时 140 毫秒
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梯级水电站优化调度对于增加系统发电量,降低耗水率,充分利用流域水能资源,提高整个梯级水电站群的经济效益和运行水平具有重要意义。建立"一库多级"梯级水电站群短期优化调度模型,研究采用逐步优化算法(POA算法)进行模型求解的方法和步骤,在此基础上开发调度软件,并以金溪流域梯级电站群为例对算法实际应用效果进行分析。研究结果表明,采用POA算法能够有效提高水电站发电量3%以上,且POA算法具有易于计算机程序实现的特点,在水电站自动优化调度方面具有较大优势。 相似文献
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在实时、复杂的网络环境中,如何激励工人参与任务并得到高质量的感知数据是时空众包研究的重点。基于此,提出一种基于质量感知的时空众包在线激励机制。首先,为了适应时空众包实时性的特点,提出一种阶段性在线选择工人算法(POA),该算法在预算约束下将整个众包活动周期分为多个阶段,每个阶段在线选择工人;其次,为了提高质量预估的精度与效率,提出一种改进的最大期望(IEM)算法,该算法在算法迭代的过程中优先考虑可信度高的工人提交的任务结果;最后,通过真实数据集上的对比实验,验证了所提激励机制在提高平台效用方面的有效性。实验结果表明,POA相较于改进的两阶段拍卖(ITA)算法、多属性与两阶段相结合的拍卖(M-ITA)算法,以及L-VCG(Lyapunov-based Vickrey-Clarke-Groves)等拍卖算法,效率平均提高了11.11%,工人的额外奖励金额平均提升了12.12%,可以激励工人向冷门偏远地区移动;在质量预估方面,IEM算法相比其他质量预估算法,在精度和效率上分别平均提高了5.06%和14.2%。 相似文献
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遗传算法的改进及其应用研究 总被引:20,自引:1,他引:19
基于工程优化命题的特点对传统遗传算法进行了改进,改进算法在尿素工业过程神经网络建模和专家系统知识获取中的应用结果表明,该算法适用范围广,可有效地解决若干工程优化问题。 相似文献
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可移植对象适配器POA模型是CORBA规范中一个核心模型,它是CORBA为了规范服务器应用程序的开发以及解决服务器程序在不同ORB产品之间无需修改地进行移植问题而提出的 ,POA策略是其关键特性。本文对POA模型中的七个标准策略的特点、应用场合以及各种策略组合进行了深入的分析,在此基础上设计实现了POA策略机制,提供了灵活的策略创建、策略管理手段,使得应用开发者可以根据需要灵活地对POA进行动态配置,从而满足了不同应用的需求。 相似文献
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蚁群优化算法的研究现状及研究展望 总被引:17,自引:0,他引:17
本文首先简要地介绍蚁群优化算法的来源、对应的生物原理和算法实现的框架.然后详细地讨论了算法的研究现状以及在各种优化问题中的应用情况,同时也指出了蚁群优化算法在当前应用中的一些不足.针对这些不足提出了解决方法,描述了几种蚁群优化算法的修正策略.最后对蚁群优化算法下一步的研究方向进行了展望. 相似文献
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改进的群搜索优化算法在MATLAB中的实现 总被引:1,自引:0,他引:1
文章介绍了一种改进的带趋势预测的群搜索优化(Group Search Optimizer,GSO)算法,描述了此算法在MATLAB中的程序实现。同时根据函数优化的概念,举例说明了改进算法在函数优化中的应用方法。 相似文献
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针对DV-Hop算法定位精度低的问题,提出了一种基于植物群落行为在DV-Hop算法中的定位方法。首先,该算法利用植物群落算法与DV-Hop算法的第2阶段相结合实现最小误差的平均跳距;其次,植物群落算法在后期求解未知节点坐标时对其值进一步优化。最后,仿真结果显示,改进算法在不增加额外开销的情况下,定位误差进一步降低,相比其他传统群智能优化算法对DV-Hop方法的改进,算法的定位精度有很大的优势。 相似文献
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The main objective of active noise control (ANC) is to provide attenuation for the environmental acoustic noise. The adaptive algorithms for ANC systems work well to attenuate the Gaussian noise; however, their performance may degrade for non-Gaussian impulsive noise sources. Recently, we have proposed variants of the most famous ANC algorithm, the filtered-x least mean square (FxLMS) algorithm, where an improved performance has been realized by thresholding the input data or by efficiently normalizing the step-size. In this paper, we propose a modified binormalized data-reusing (BNDR)-based adaptive algorithm for impulsive ANC. The proposed algorithm is derived by minimizing a modified cost function, and is based on reusing the past and present samples of data. The main contribution of the paper is to develop a practical DR-type adaptive algorithm, which incorporates an efficiently normalized step-size, and is well suited for ANC of impulsive noise sources. The computer simulations are carried out to demonstrate the effectiveness of the proposed algorithm. It is shown that an improved performance has been realized with a reasonable increase in the computational complexity. 相似文献
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ABSTRACTThe freely available global and near-global digital elevation models (DEMs) have shown great potential for various remote sensing applications. The Shuttle Radar Topography Mission (SRTM) data sets provide the near-global DEM of the Earth’s surface obtained using the interferometry synthetic aperture radar (InSAR). Although free accessibility and generality are the advantages of these data sets, many applications require more detailed and accurate DEMs. In this paper, we proposed a modified and advanced polarimetry-clinometry algorithm for improving SRTM topography model which requires only one set of polarimetric synthetic aperture radar (PolSAR) data. The azimuth and range slope components estimation based on polarization orientation angle (POA) shifts and the intensity-based Lambertian model formed the bases of the proposed method. This method initially compensated for the polarimetry topography effect corresponding to SRTM using the DEM-derived POA. In the second step, using a modified algorithm, POA was obtained from the compensated PolSAR data. The POA shifts by the azimuth and range slopes’ variations based on the polarimetric model. In addition to the polarimetric model, a clinometry model based on the Lambertian scattering model related to the terrain slope was employed. Next, two unknown parameters, i.e. azimuth and range slope values, were estimated in a system of equations by two models from the compensated PolSAR data. Azimuth and range slopes of SRTM were enhanced by PolSAR-derived slopes. Finally, a weighted least-square grid adjustment (WLSG) method was proposed to integrate the enhanced slopes’ map and estimate enhanced heights. The National Aeronautics and Space Administration Jet Propulsion Laboratory (NASA JPL) AIRSAR was utilized to illustrate the potential of the proposed method in SRTM enhancement. Also, the InSAR DEM was employed for evaluation experiments. Results showed that the accuracy of SRTM DEM is improved up to 2.91 m in comparison with InSAR DEM. 相似文献
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This paper considers uncertain constrained systems, and develops two algorithms for computing a probabilistic output admissible (POA) set which is a set of initial states probabilistically assured to satisfy the constraint. The first algorithm is inspired by an existing randomized sequential technique. The second algorithm alleviates the computational effort based on heuristics. The present algorithms terminate in a finite number of iterations and provide a POA set. Additionally, we can obtain information on the size of the resulting set a posteriori. A numerical simulation demonstrates the applicability of the POA set to a control system design scheme. 相似文献
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Vector quantization of images using modified adaptive resonancealgorithm for hierarchical clustering 总被引:3,自引:0,他引:3
A modified adaptive resonance theory (ART2) learning algorithm, which we employ in this paper, belongs to the family of NN algorithms whose main goal is the discovery of input data clusters, without considering their actual size. This feature makes the modified ART2 algorithm very convenient for image compression tasks, particularly when dealing with images with large background areas containing few details. Moreover, due to the ability to produce hierarchical quantization (clustering), the modified ART2 algorithm is proved to significantly reduce the computation time required for coding, and therefore enhance the overall compression process. Examples of the results obtained are presented, suggesting the benefits of using this algorithm for the purpose of VQ, i.e., image compression, over the other NN learning algorithms. 相似文献
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Xiaoge Zhang Yajuan Zhang Yong Hu Yong Deng Sankaran Mahadevan 《Expert systems with applications》2013,40(18):7607-7616
The constrained shortest path problem (CSP) is one of the basic network optimization problems, which plays an important part in real applications. In this paper, an adaptive amoeba algorithm is combined with the Lagrangian relaxation algorithm to solve the CSP problem. The proposed method is divided into two steps: (1) the adaptive amoeba algorithm is modified to solve the shortest path problem (SPP) in a directed network; (2) the modified adaptive amoeba algorithm is combined with the Lagrangian relaxation method to solve the CSP problem. In addition, the evolving processes of the adaptive amoeba model have been detailed in the paper. Two examples are used to illustrate the efficiency of the proposed method. The results show that the proposed method can deal with the CSP problem effectively. 相似文献