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An improved particle swarm optimization for feature selection [PDF]
Intelligent Data Analysis, 2012 Searching for an optimal feature subset in a high-dimensional feature space is an NP-complete problem; hence, traditional optimization algorithms are inefficient when solving large-scale feature selection problems. Therefore, meta-heuristic algorithms have been extensively adopted to solve the feature selection problem efficiently.
Li-Fei Chen, Chao-Ton Su, Kun-Huang Chen
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An improved particle swarm optimizer with momentum
2007 IEEE Congress on Evolutionary Computation, 2007In this paper, an improved particle swarm optimization algorithm with momentum (mPSO) is proposed based on inspiration from the back propagation (BP) learning algorithm with momentum in neural networks. The momentum acts as a lowpass filter to relieve excessive oscillation and also extends the PSO velocity updating equation to a second-order difference
Tao Xiang 0001 +2 more
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Improvement of Particle Swarm Optimization
PIERS Online, 2009A new technique titled \Particle Refresh" and a hybridization with conjugate gradient method are introduced to particle swarm optimization (PSO). The former charges power to inactive particle to improve the recovery ability of PSO after trapping on a local solution, and as a result, it becomes easy to choose suitable values for control-parameters to ...
K. Kawakami, Zhi Qi Meng
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Improving Particle Swarm Optimization of Its Convergence
2020 5th International Conference on Control, Robotics and Cybernetics (CRC), 2020There are few controllable parameters in the particle swarm optimization algorithm and its value is fixed, it has some problems such as premature convergence and falling into local optimal solutions. In this paper, an improved particle swarm optimization algorithm is proposed.
Zuyuan Huang, Guohong Yi, Bangbang Liu
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Improved Particle Swarm Optimization algorithms for electromagnetic optimization
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, 2008Particle Swarm is a relatively novel approach for global stochastic optimization. In this paper some variations over the basic algorithm are proposed, with the aim of a more efficient search over the solution space obtained with a negligible overhead in both complexity and speed. The presented algorithms are then applied to a mathematical test function
MUSSETTA, MARCO +4 more
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An Improved Particle Swarm Optimizer for Truss Structure Optimization
2006 International Conference on Computational Intelligence and Security, 2006This paper presents an improved particle swarm optimizer (IPSO) for solving truss structure optimization problems. The algorithm is based on the particle swarm optimizer with passive congregation (PSOPC) and a harmony search (HS) scheme. It handles the problem-specified constraints using a `fly-back mechanism' method and the variables' constraints ...
Lijuan Li, Zhibin Huang, Feng Liu 0052
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Constrained optimization with an improved particle swarm optimization algorithm
International Journal of Intelligent Computing and Cybernetics, 2008PurposeThe purpose of this paper is to present a new constrained optimization algorithm based on a particle swarm optimization (PSO) algorithm approach.Design/methodology/approachThis paper introduces a hybrid approach based on a modified ring neighborhood with two new perturbation operators designed to keep diversity.
Angel Eduardo Muñoz-Zavala +3 more
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An improved cooperative particle swarm optimizer
Telecommunication Systems, 2013Particle Swarm Optimization (PSO) is a population-based technique for optimization, which simulates the social behavior of the bird flocking, a novel Adaptive Cooperative PSO (ACPSO) with adaptive search is presented in this paper, the proposed approach combines both cooperative learning and PSO with adaptive inertia weight, cooperative learning is ...
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An Improved Particle Swarm Optimization Algorithm
2019Based on a brief introduction to the principle of particle swarm optimization (PSO) and different improved methods of PSO at home and abroad, the particle swarm optimization algorithm is improved for the shortcomings of particle swarm optimization.
Chunguang Chang, Xi Wu
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An improved particle swarm optimization algorithm with disturbance
2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583), 2005The impacts of constant parameters on particle swarm optimization are discussed. A velocity or position disturbance is introduced to prevent premature phenomenon of the original algorithm. A valve is introduced and the selection criteria are discussed. Simulations have been carried and the results show this improved algorithm has better performance by ...
Wei Jian, Yuncan Xue, Jixin Qian
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