Results 1 to 10 of about 1,332 (147)
A fast PSO algorithm based on Alpha-stable mutation and its application in aerodynamic optimization
Xibei Gongye Daxue Xuebao, 2022 提出了一种基于Alpha stable分布的新型变异方法。针对粒子群算法容易陷入局部最优的缺点, 通过对比分析确定了一种调整Alpha stable分布的稳态系数动态变异策略, 使粒子群算法能够在搜索初始阶段具有更强的种群多样性以及算法探索能力, 减少陷入局部最优的可能; 在算法末期增强粒子群优化算法的局部搜索能力, 提高解的精度。将基于Alpha stable变异的粒子群优化算法(Alpha stable particle swarm optimization, ASPSO ...
FAN Huayu +3 more
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Energy efficiency optimization algorithm of heterogeneous networks based on hybrid energy supply and energy cooperation [PDF]
, 2022 To reduce the base station energy consumption and co-channel interference in heterogeneous cellular networks, a joint optimization algorithm combined with energy harvesting and energy cooperation was proposed with the objective of energy efficiency ...
Chunling PENG +3 more
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智能科学与技术学报, 2022 针对含分布式电源（DG）的配电网动态重构问题，提出考虑配电网负荷需求与 DG 出力动态变化的配电网动态重构方案。首先，基于不同时段的负荷特性与最优网络结构的综合相似性，提出了一种改进层次聚类的时段划分方法。在此基础上，提出了遗传学习自适应粒子群优化算法，实现以网络损耗最小为优化目标的动态重构优化计算。针对基本粒子群算法中缺乏速度动态调节、易陷入局部最优等问题，提出基于粒子个体最优位置的遗传学习方案增加搜索多样性，提高算法的全局搜索能力，并引入自适应惯性权值和加速系数以满足不同时期的寻优要求。最后 ...
王云 +4 more
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Study of the ternary correlation quantum-behaved PSO algorithm [PDF]
, 2015 In order to more effectively utilize existing information and improve QPSO's (quantum-behaved particle swarm optimization) convergence performance, the ternary correlation QPSO (TC-QPSO) algorithm was proposed based on the analysis of the random factors ...
Tao WU, Xi CHEN, Yu-song YAN
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智能科学与技术学报, 2022 供应链网络通过需求和供应关系将各个成员连接起来，方便成员之间进行协调与合作，这在全球化竞争环境下显得尤为重要。对供应链网络结构进行优化改进能够缩小企业运营成本、提高企业收益，提升客户满意度，进而提高企业的竞争力。首先，通过分析供应链网络中的优化问题，从建模特征、决策变量类型和场景特征等不同角度对该问题进行分类，从而更清晰地介绍现有供应链网络研究工作中涉及的优化问题。然后，介绍并分析了遗传算法、蚁群优化算法和粒子群优化算法3种常用的智能优化算法及其在供应链网络优化问题中的应用情况。最后 ...
张欣, 詹志辉
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Adaptive fractional-order Darwinian particle swarm optimization algorithm [PDF]
, 2014 The convergence performance of the fractional-order Darwinian particle swarm optimization (FO-DPSO) al-gorithm depends on the fractional-order α, and it can easily get trapped in the local optima.
Ju-long LAN +3 more
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Zhejiang Daxue xuebao. Lixue ban, 2018 针对粒子群算法容易陷入局部最优解的问题，提出了一种基于动态分级和邻域反向学习的改进粒子群算法.该算法通过构建动态分级机制，将种群中的粒子动态地划分成3个等级，对不同等级内的粒子采取不同的扰动行为，使得粒子在增强种群多样性的同时保持向全局最优方向进化；采用粒子智能更新方式，提高了粒子的搜索能力；引入动态邻域反向学习点建立全局搜索策略，促使种群快速寻优.最后，利用多种典型测试函数对该算法进行仿真实验，结果表明，与其他几种优化算法相比，本算法具有较好的收敛性和稳定性.
RENYanzhi(任燕芝)
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Zhejiang Daxue xuebao. Lixue ban, 2016 为提高粒子群算法的收敛速度和优化性能，避免陷入局部最优，提出了一种基于动态学习因子和共享适应度函数的改进粒子群算法.在惯性权重w随着迭代次数非线性减少而动态调整学习因子的基础上，引入共享适应度函数.当算法未达到终止条件而收敛时，利用粒子和最优解间距离挑选一批粒子重新初始化形成新群体，并用共享适应度函数对新群体进行评价，新旧2个群体分别追随自己的局部最优解直至迭代结束.对4个典型多峰复杂函数的测试结果表明，该改进算法不仅加快了寻得最优解的速度，而且提高了粒子群算法全局收敛的性能.
TANYifeng(谭熠峰) +2 more
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Improved PSO algorithm based on swarm prematurely degree and nonlinear periodic oscillating strategy [PDF]
, 2014 A novel particle swarm optimization algorithm was proposed, which was adaptive chaos particle swarm opti-mization algorithm based on swarm premature convergence degree and nonlinear periodic oscillating strategy.
Bing-kui FAN +3 more
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Improved SMC cardinality-balanced multi-Bernoulli forwardbackward smoothing track-before-detect algorithm [PDF]
, 2019 For the tracking problem of multiple maneuvering targets in radar observation,the sequential Monte-Carlo cardinality-balanced multi-Bernoulli track-before-detect (SMC-CBMeMBer-TBD) algorithm is inaccurate in the estimation of the number of targets and ...
Jiazheng PEI +3 more
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