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关键词

粒子群优化算法 2

BFT 1

优化调度 1

信息素 1

协同功效系数 1

协同碰撞避免系统；改进的粒子群算法；PID控制器；行驶舒适性；燃油经济性 1

合成孔径 1

吸气式高超声速飞行器；随机鲁棒性分析；二次线性调节器；粒子群优化；改进混合粒子群算法 1

响应预测 1

多目标协同规划模型 1

工程项目管理 1

微粒群算法 1

旅行商问题 1

最小二乘支持向量机 1

毫米波辐射计 1

水文科学 1

水电站厂房 1

算例 1

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Solution to economic dispatch problem with valve-point loading effect by using catfish PSO algorithm

K. MURALI,T. JAYABARATHI

《能源前沿（英文）》 2014年第8卷第3期页码 290-296 doi: 10.1007/s11708-014-0305-y

摘要： This paper proposes application of a catfish particle swarm optimization (PSO) algorithm to economic dispatch (ED) problems. The ED problems considered in this paper include valve-point loading effect, power balance constraints, and generator limits. The conventional PSO and catfish PSO algorithms are applied to three different test systems and the solutions obtained are compared with each other and with those reported in literature. The comparison of solutions shows that catfish PSO outperforms the conventional PSO and other methods in terms of solution quality though there is a slight increase in computational time.

关键词： economic dispatch (ED) valve point loading catfish particle swarm optimization (PSO) optimization

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Power system reconfiguration and loss minimization for a distribution systems using “Catfish PSO” algorithm

K Sathish KUMAR,S NAVEEN

《能源前沿（英文）》 2014年第8卷第4期页码 434-442 doi: 10.1007/s11708-014-0313-y

摘要： One of the very important ways to save electrical energy in the distribution system is network reconfiguration for loss reduction. Distribution networks are built as interconnected mesh networks; however, they are arranged to be radial in operation. The distribution feeder reconfiguration is to find a radial operating structure that optimizes network performance while satisfying operating constraints. The change in network configuration is performed by opening sectionalizing (normally closed) and closing tie (normally opened) switches of the network. These switches are changed in such a way that the radial structure of networks is maintained, all of the loads are energized, power loss is reduced, power quality is enhanced, and system security is increased. Distribution feeder reconfiguration is a complex nonlinear combinatorial problem since the status of the switches is non-differentiable. This paper proposes a new evolutionary algorithm (EA) for solving the distribution feeder reconfiguration (DFR) problem for a 33-bus and a 16-bus sample network, which effectively ensures the loss minimization.

关键词： distribution system reconfiguration (DFR) power loss reduction catfish particle swarm optimization (catfish PSO) radial structure

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A hybrid BFA-PSO algorithm for economic dispatch with valve-point effects

T. Jayabarathi, Prateek Bahl, Harsha Ohri, Afshin Yazdani, V. Ramesh

《能源前沿（英文）》 2012年第6卷第2期页码 155-163 doi: 10.1007/s11708-012-0189-7

摘要： This paper presents a novel and efficient method for solving the economic dispatch (ED) problems with valve-point effects, by integrating the biased velocity of particle swarm optimization (PSO) to the chemotaxis, swarming and reproduction steps of bacterial foraging algorithm (BFA). To include valve point effects sinusoidal terms are added to the fuel cost function. This makes the ED problems highly non-linear. In order to solve such problems the best cell (or particle) biased velocity (vector) is added to the random velocity of the BFA to reduce randomness in movement (evolution) and to increase swarming. This results in the hybrid bacterial foraging algorithm (HBFA). To demonstrate the effectiveness of the proposed HBFA method, numerical studies have been performed for three different sample systems. Comparison of the results obtained by the HBFA with the BFA and other evolutionary algorithms clearly show that the proposed method outperforms other methods in terms of convergence rate and solution quality in solving the ED problems with valve-point effects.

关键词： bacterial foraging algorithm (BFA) economic dispatch (ED) particle swarm optimization (PSO) valve-point effects

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Water quality prediction of copper-molybdenum mining-beneficiation wastewater based on the PSO-SVR model

《环境科学与工程前沿（英文）》 2023年第17卷第8期 doi: 10.1007/s11783-023-1698-9

摘要：

● Data acquisition and pre-processing for wastewater treatment were summarized.

关键词： Chemical oxygen demand Mining-beneficiation wastewater treatment Particle swarm optimization Support vector regression Artificial neural network

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基于随机鲁棒性分析的吸气式高超声速飞行器线性二次调节器设计 Article

Lin CAO, Shuo TANG, Dong ZHANG

《信息与电子工程前沿（英文）》 2017年第18卷第7期页码 882-897 doi: 10.1631/FITEE.1601363

摘要：吸气式高超声速飞行器（air-breathing hypersonic vehicle, AHV）的飞行动力学模型具有高度非线性与多变量耦合等特性，且受到内部不确定性与外部干扰的综合影响，因此需要具有强鲁棒性与高精度的控制器。本文介绍了一种改进的基于随机鲁棒性分析的线性二次调节器（linear-quadratic regulator, LQR）设计方法，用于AHV的纵向飞行控制器设计。首先，应用输入输出反馈线性化技术设计LQR控制器。其次，基于系统参数的不确定性，将系统鲁棒性表征为满足稳定性与设计指标要求的概率，并构建系统鲁棒性与LQR参数之间的映射关系。为了实现系统鲁棒性最大化的目标，提出一种全新的混合粒子群优化算法对LQR的控制参数进行寻优计算。在优化迭代的过程中，使用切诺夫边界理论确定蒙特卡洛估计的随机样本量。最后，仿真结果表明该优化算法可以高效地获取满足设计要求的LQR控制参数最优解。

关键词：吸气式高超声速飞行器；随机鲁棒性分析；二次线性调节器；粒子群优化；改进混合粒子群算法

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基于PSO优化LS-SVM算法的水电站厂房结构振动响应预测

练继建,何龙军,王海军

《中国工程科学》 2011年第13卷第12期页码 45-50

摘要：

依据二滩水电站地下厂房和机组的原型观测数据对机组和厂房结构振动的相关性进行分析，据此建立基于粒子群优化最小二乘支持向量计算法的厂房振动响应预测模型，预测结果与实测资料吻合。在此基础上将运行水头作为输入因子引入到智能预测模型中，扩大了该智能预测模型的适用范围，取得了很好的效果。

关键词：水电站厂房耦联振动粒子群优化算法最小二乘支持向量机响应预测

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收回说明：使用基于多目标PSO的分层ANFIS控制器-TCSC增强互连多电源系统的动态稳定性 Retraction Note

null

《信息与电子工程前沿（英文）》 2019年第20卷第5期 doi: 10.1631/FITEE.19r0001

摘要： None

关键词： None

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Ranking of design scenarios of TMD for seismically excited structures using TOPSIS

Sadegh ETEDALI

《结构与土木工程前沿（英文）》 2020年第14卷第6期页码 1372-1386 doi: 10.1007/s11709-020-0671-y

摘要： In this paper, design scenarios of a tuned mass damper (TMD) for seismically excited structures are ranked. Accordingly, 10 design scenarios in two cases, namely unconstrained and constrained for the maximum TMD, are considered in this study. A free search of the TMD parameters is performed using a particle swarm optimization (PSO) algorithm for optimum tuning of TMD parameters. Furthermore, nine criteria are adopted with respect to functional, operational, and economic views. A technique for order performance by similarity to ideal solution (TOPSIS) is utilized for ranking the adopted design scenarios of TMD. Numerical studies are conducted on a 10-story building equipped with TMD. Simulation results indicate that the minimization of the maximum story displacement is the optimum design scenario of TMD for the seismic-excited structure in the unconstrained case for the maximum TMD stroke. Furthermore, H of the displacement vector of the structure exhibited optimum ranking among the adopted design scenarios in the constrained case for the maximum TMD stroke. The findings of this study can be useful and important in the optimum design of TMD parameters with respect to functional, operational, and economic perspectives.

关键词： seismic-excited building TMD optimum design PSO design scenario TOPSIS

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Constriction factor based particle swarm optimization for analyzing tuned reactive power dispatch

Syamasree BISWAS(RAHA), Kamal Krishna MANDAL, Niladri CHAKRABORTY

《能源前沿（英文）》 2013年第7卷第2期页码 174-181 doi: 10.1007/s11708-013-0246-x

摘要： The reactive power dispatch (RPD) problem is a very critical optimization problem of power system which minimizes the real power loss of the transmission system. While solving the said problem, generator bus voltages and transformer tap settings are kept within a stable operating limit. In connection with the RPD problem, solving reactive power is compensated by incorporating shunt capacitors. The particle swarm optimization (PSO) technique is a swarm intelligence based fast working optimization method which is chosen in this paper as an optimization tool. Additionally, the constriction factor is included with the conventional PSO technique to accelerate the convergence property of the applied optimization tool. In this paper, the RPD problem is solved in the case of the two higher bus systems, i.e., the IEEE 57-bus system and the IEEE 118-bus system. Furthermore, the result of the present paper is compared with a few optimization technique based results to substantiate the effectiveness of the proposed study.

关键词： real power loss minimization voltage stability constriction factor particle swarm optimization (PSO)

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利用改进粒子群求解TSP 问题的一种新方法

成伟明,唐振民,赵春霞,陈得宝

《中国工程科学》 2008年第10卷第7期页码 165-168

摘要：

借鉴蚁群算法中的信息素机制，并利用粒子群算法操作简单、易于实现、计算量小的特点，给出一种新的求解TSP问题方法。对基本粒子群算法进行了改进，针对多样性下降导致的局部最优问题，设计了一种自动调节机制。根据群体适应度的差异计算多样性，并在群体多样性下降到一定程度时，随机退化部分适应值较高的粒子，增强群体的多样性。通过对旅行商问题的对比实验验证了该方法的有效性。

关键词：信息素粒子群优化旅行商问题

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Estimation of distribution algorithm enhanced particle swarm optimization for water distribution network optimization

Xuewei QI,Ke LI,Walter D. POTTER

《环境科学与工程前沿（英文）》 2016年第10卷第2期页码 341-351 doi: 10.1007/s11783-015-0776-z

摘要： The optimization of a water distribution network (WDN) is a highly nonlinear, multi-modal, and constrained combinatorial problem. Particle swarm optimization (PSO) has been shown to be a fast converging algorithm for WDN optimization. An improved estimation of distribution algorithm (EDA) using historic best positions to construct a sample space is hybridized with PSO both in sequential and in parallel to improve population diversity control and avoid premature convergence. Two water distribution network benchmark examples from the literature are adopted to evaluate the performance of the proposed hybrid algorithms. The experimental results indicate that the proposed algorithms achieved the literature record minimum (6.081 M$) for the small size Hanoi network. For the large size Balerma network, the parallel hybrid achieved a slightly lower minimum (1.921M?) than the current literature reported best minimum (1.923M?). The average number of evaluations needed to achieve the minimum is one order smaller than most existing algorithms. With a fixed, small number of evaluations, the sequential hybrid outperforms the parallel hybrid showing its capability for fast convergence. The fitness and diversity of the populations were tracked for the proposed algorithms. The track record suggests that constructing an EDA sample space with historic best positions can improve diversity control significantly. Parallel hybridization also helps to improve diversity control yet its effect is relatively less significant.

关键词： particle swarm optimization (PSO) diversity control estimation of distribution algorithm (EDA) water distribution network (WDN) premature convergence hybrid strategy

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粒子群优化算法在水文科学中的应用进展

董前进,曹广晶,王先甲,戴会超,赵云发

《中国工程科学》 2010年第12卷第1期页码 81-85

摘要：

介绍了粒子群算法的标准算法及流程，探讨了粒子群算法在水库优化调度、水电站经济运行、参数优选等水文领域中的研究成果和存在的问题，指出未来应该加强粒子群算法改进机理和收敛性能的研究，并与其他算法技术相比较、结合，拓展其在水文科学领域的应用范围，为解决水文领域中大量优化问题提供新途径。

关键词：水文科学粒子群优化算法优化调度经济运行

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工程项目多目标协同优化研究

刘晓峰,陈通,吴绍艳

《中国工程科学》 2010年第12卷第3期页码 90-94

摘要：

将微粒群算法(particle swarm optimization，PSO)引入工程项目多目标协同优化领域，研究工程项目的质量、费用、资源和工期的协同优化问题

关键词：微粒群算法工程项目管理协同功效系数多目标协同规划模型算例

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近程毫米波合成孔径辐射计被动测距原理

王本庆,李兴国

《中国工程科学》 2010年第12卷第3期页码 95-99

摘要：

毫米波合成孔径技术利用了物体自身辐射电磁波的相位信息，采用很少阵元就能实现实时成像，但目前合成孔径技术只是限于亮温成像，缺少了目标的距离信息，这对于目标探测与识别很不利。提出在近程条件下合成孔径被动测距原理和相应的双正交傅立叶变换算法，并给出了近程距离分辨率公式，近程成像的特点是成像公式中存在二次相位因子，而且距离分辨率和距离的平方成反比。毫米波合成孔径被动成像可以同时得到物体辐射的亮温分布和距离分布，能够有效克服离焦引起的图像模糊，对图像的反降晰和目标识别具有重要意义。

关键词：毫米波辐射计合成孔径近程成像被动测距 BFT