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Multi-objective optimization design of oil spray cooling system for hairpin motor based on particle swarm optimization-backpropagation-non-dominated sorting genetic algorithm III. [PDF]

Sci Rep
Liu Y, Xu P, Chen S, Li S, Zhang J, Liu T.   +5 more
europepmc   +1 more source

Particle swarm optimization-based NLP methods for optimizing automatic document classification and retrieval. [PDF]

PLoS One
Zeng B, Shang X, Lu R, Zhang Y.
europepmc   +1 more source

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Cellular particle swarm optimization

Information Sciences, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hongcheng Liu, Liang Gao, Guohui Zhang   +2 more
exaly   +3 more sources

Heterogeneous particle swarm optimizers [PDF]

2009 IEEE Congress on Evolutionary Computation, 2009
Particle swarm optimization (PSO) is a swarm intelligence technique originally inspired by models of flocking and of social influence that assumed homogeneous individuals. During its evolution to become a practical optimization tool, some heterogeneous variants have been proposed.
Marco Antonio Montes de Oca, Jorge Peña 0001, Thomas Stützle, Carlo Pinciroli, Marco Dorigo   +4 more
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Particle swarm optimization

Proceedings of ICNN'95 - International Conference on Neural Networks, 2002
A concept for the optimization of nonlinear functions using particle swarm methodology is introduced. The evolution of several paradigms is outlined, and an implementation of one of the paradigms is discussed. Benchmark testing of the paradigm is described, and applications, including nonlinear function optimization and neural network training, are ...
James Kennedy, Russell Eberhart
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Clan Particle Swarm Optimization

2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence), 2008
PurposeParticle swarm optimization (PSO) has been used to solve many different types of optimization problems. In spite of this, the original version of PSO is not capable to find reasonable solutions for some types of problems. Therefore, novel approaches to deal with more sophisticated problems are required. Many variations of the basic PSO form have
Danilo Ferreira de Carvalho, Carmelo J. A. Bastos Filho   +1 more
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Visualizing particle swarm optimization - Gaussian particle swarm optimization

Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706), 2004
Particle swarm optimization (PSO) conjures an image of particles searching for the optima the way bees buzz around flowers. One approach at visualizing the swarm graphs where all the particles are each generation, thus demonstrating the random nature associated with swarms of insects.
Barry R. Secrest, Gary B. Lamont
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Compact Particle Swarm Optimization

Information Sciences, 2013
Some real-world optimization problems are plagued by a limited hardware availability. This situation can occur, for example, when the optimization must be performed on a device whose hardware is limited due to cost and space limitations. This paper addresses this class of optimization problems and proposes a novel algorithm, namely compact Particle ...
Ferrante Neri, Ernesto Mininno, Giovanni Iacca   +2 more
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Individualism of particles in particle swarm optimization

Applied Soft Computing, 2019
Abstract The particle swarm optimization (PSO) method is an effective, nature-inspired, computational algorithm for optimization problems. However, the influence of individuals’ cultural orientations is neglected in particle swarms. Individualist and collectivist orientations have an important influence on optimization.
Kun Miao, Xiaolin Mao, Chen Li
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Grey particle swarm optimization

Applied Soft Computing, 2012
With the help of grey relational analysis, this study attempts to propose two grey-based parameter automation strategies for particle swarm optimization (PSO). One is for the inertia weight and the other is for the acceleration coefficients. By the proposed approaches, each particle has its own inertia weight and acceleration coefficients whose values ...
Min-Shyang Leu, Ming-Feng Yeh
openaire   +1 more source