Results 231 to 240 of about 17,803 (264)

An Improved Particle Swarm Algorithms for Global Optimization

2010 International Conference on Machine Vision and Human-machine Interface, 2010
Particle swarm optimization (PSO) algorithm is a robust and efficient approach for solving complex real-world problems. In this paper, a modified particle swarm algorithm (IMPSO) is introduced for unconstrained global optimization. The whole swarm is partitioned to three different sub-populations according to their fitness, and different velocity ...
Ye Tian, Dayou Liu
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An improved Particle Swarm Optimization with adaptive jumps

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), 2008
Particle swarm optimization (PSO) has shown its fast search speed in many complicated optimization and search problems. However, PSO could often easily fall into local optima. This paper presents an improved PSO with adaptive jump. The proposed method combines a novel jump strategy and an adaptive Cauchy mutation operator to help escape from local ...
Hui Wang 0002, Yong Liu 0012, Zhijian Wu, Hui Sun 0001, Sanyou Zeng, Lishan Kang   +5 more
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An improved Michigan particle swarm optimization for classification

2011 IEEE Symposium on Swarm Intelligence, 2011
Classification is one of the most frequently occurring tasks of human decision making. In this paper, two improved versions of Michigan particle swarm optimization (MPSO), Improved MPSO1 (IMPSO1) and Improved MPSO2 (IMPSO2), are proposed. IMPSO1 adopts a adaptive inertia factor so as to flexibly control the search path, moreover, both nearest neighbor (
Pei Wu, Ruochen Liu 0006, Jingjing Ma 0001, Yangyang Li 0001   +3 more
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A New Improved Particle Swarm Optimization Algorithm

2011 Seventh International Conference on Computational Intelligence and Security, 2011
To improve PSO, differential evolution (DEA) and ant colony strategy are involved into PSO algorithm, and new PSO(DAPSO) is presented. Handling the current optimal positions of particles with differential evolution, the detecting and exploitation ability of both PSO and DEA are utilized effectively, and some potential evolution directions are ...
Yuhong Duan, Yuelin Gao
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An Improved Diversity Guided Particle Swarm Optimization

2009
Particle swarm optimization (PSO) is a new population based stochastic search algorithm, which has shown good performance on well-known numerical test problems. However, on strongly multimodal test problems the PSO easily suffers from premature convergence.
Dongsheng Xu, Xiaoyan Ai
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The Analysis and Improvement of Binary Particle Swarm Optimization

2009 International Conference on Computational Intelligence and Security, 2009
In this paper, the binary Particle Swarm Optimization (PSO) is analyzed with bit change rate and velocity expected value, which results is that binary PSO is more and more stochastic, has the powerful ability of global search, but cannot converge to the optimal particle of swarm.
Jianhua Liu, Xiaoping Fan
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An Improved Particle Swarm Optimization for SVM Training

Third International Conference on Natural Computation (ICNC 2007), 2007
Since training a SVM requires solving a constrained quadratic programming problem which becomes difficult for very large datasets, an improved particle swarm optimization algorithm is proposed as an alternative to current numeric SVM training methods. In the improved algorithm, the particles studies not only from itself and the best one but also from ...
Ying Li 0017, Yan Tong, Bendu Bai, Yanning Zhang 0001   +3 more
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Improvement and application of particle swarm optimization algorithm

Intelligent Decision Technologies
Particle Swarm Optimization (PSO) remains straightforward and has many scientific and engineering applications. Most real-world optimization problems are nonlinear and discrete with local constraints. The PSO algorithm encounters issues such as inefficient solutions and early convergence.
Durga Praveen Deevi, Sharadha Kodadi, Naga Sushma Allur, Koteswararao Dondapati, Himabindu Chetlapalli, Thinagaran Perumal   +5 more
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Improved Exploration and Exploitation in Particle Swarm Optimization

2018
Exploration and exploitation are analyzed in Particle Swarm Optimization (PSO) through a set of experiments that make new measurements of these key features. Compared to analyses on diversity and particle trajectories, which focus on particle motions and their potential to achieve exploration and exploitation, our analysis also focuses on the pbest ...
Dania Tamayo-Vera, Stephen Chen 0001, Antonio Bolufé Röhler, James Montgomery 0001, Tim Hendtlass   +4 more
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An Improved Particle Swarm Optimization

2009 2nd International Conference on Biomedical Engineering and Informatics, 2009
Qin Yang, Danyang Wang
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