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针对果蝇优化算法( FOA)收敛速度快但寻优精度低的缺点,为了改善果蝇算法的优化性能,提出一种混合果蝇优化算法( HFOA)。HFOA采用分段优化的思想,在优化过程后期采用收敛稳定性较好的粒子群优化( PSO)算法优化果蝇算法中果蝇个体飞行距离和味道浓度的判定值,采用误差性能指标积分准则ITAE作为适应度函数,并将优化方案应用于一类不稳定系统的PID控制。Matlab仿真验证表明:HFOA计算高效,具有良好的稳定性,收敛精度高,进而验证了HFOA应用于PID控制参数优化是可行而有效的。 相似文献
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针对采用传统算法对开关磁阻电机(SRM)本体进行多目标优化时存在算法复杂、调节参数多、计算量大且易陷入局部最优解等问题,提出一种基于果蝇算法(FOA)的SRM本体多目标优化设计方法。利用极限学习机算法建立SRM非参数模型,采用FOA算法对其进行优化,实现了SRM定转子极弧的全局最优设计,最后对该优化算法的效果进行了仿真验证,同时与传统粒子群优化算法(PSO)进行了对比分析,结果表明,FOA算法不仅获得了较PSO算法更好的转矩波动系数和效率指标,而且具有参数设置少、收敛速度快且不易陷入局部最优解等特点,具有较好的应用价值。 相似文献
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Bum Suk Kim Maksym Spiryagin Bong Soo Kim Hong Hee Yoo 《Journal of Mechanical Science and Technology》2009,23(4):960-963
In the design process of an automobile part, several analysis methods are usually used to evaluate the performance of the
part. However, most automobile design engineers do not directly use CAE (computer aided engineering) tools since specific
skills are required to obtain practical results. Moreover, CAE requires a huge amount of computation time and cost. To resolve
these problems, a new design approach, termed first order analysis (FOA), has been proposed. In this paper, the FOA technique
is employed to design a vehicle sub-frame. An equivalent model of the vehicle subframe which only consists of beam elements
is proposed and the modal properties obtained with the model are compared to those obtained with a full scale finite element
model. The effects of some parameter variations on the modal characteristics of the vehicle sub-frame are investigated by
employing the FOA equivalent model.
This paper was presented at the 4th Asian Conference on Multibody Dynamics(ACMD2008), Jeju, Korea, August 20–23, 2008.
Hong Hee Yoo graduated from the Department of Mechanical Design and Production Engineering at Seoul National University in 1980 and received
his Master’s degree from the same department in 1982. He received his Ph.D. degree in 1989 from the Department of Mechanical
Engineering and Applied Mechanics at the University of Michigan at Ann Arbor, U.S.A. He is currently working as a professor
in the School of Mechanical Engineering in Hanyang University, Seoul, Korea. 相似文献
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针对管道内腐蚀速率相关问题,采集某输油管道内腐蚀的实测数据,应用多元统计分析算法,在支持向量机(SVM)的基础上建立管道内腐蚀速率预测模型。采用果蝇优化算法(FOA)对预测模型进行优化训练,建立FOASVM预测模型,利用实测数据样本对模型的预测结果进行检验。结果表明:综合方差和均差分别为1.397×10-3和0.037 4,FOA-SVM预测模型相比灰色组合模型预测值和最小二乘支持向量机(LS-SVM)模型预计结果稳定性好、精度高,但是FOA-SVM预测模型训练时间较长,今后在提高模型预测效率上需要进一步研究。 相似文献
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针对传统基于物品的推荐算法由于数据稀疏性导致的低推荐精度问题,提出了一种融合GMM聚类和FOA-GRNN模型的推荐算法。该算法首先使用高斯混合模型(GMM)方法对物品特征进行聚类;然后根据聚类结果分别构造评分矩阵,并使用Slope One算法填充评分矩阵;最后计算用户对物品的相似度预测评分作为输入,通过FOA-GRNN模型输出最终的评分。基于movielens-2k数据集的实验结果表明,与其他3种算法相比,该算法能够更好地处理高稀疏性数据,推荐精度更优,并能够在一定程度上解决冷启动问题。 相似文献
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Kevin Kennon 《Architectural Design》2006,76(5):50-53
Bringing together a number of design celebrities, among them Greg Lynn, UN Studio, Foreign Office Architects (FOA) and Kevin Kennon Architect, United Architects (UA) was established to create a collaborative proposal for the 2003 competition for a new World Trade Center. Invoking the name as well as the intentions of what started as a similar collaborative formation by established actors and film-makers in the 1940s (United Artists) to challenge mainstream corporate power, UA attempted to offer more visionary alternatives to the expectations of typical mainstream architectural solutions. Kevin Kennon here presents an insider's perspective on the UA collaboration and employs his unique history, including his former partnership at Kohn Pedersen Fox (KPF) to raise important questions about collective design in terms of authorship, identity and practice. Central to his observations are the differences between the efficiency models of corporate teams and truly collaborative endeavours. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
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