Results 241 to 250 of about 82,578 (301)

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

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

Some of the next articles are maybe not open access.

Related searches:

Cellular particle swarm optimization

Information Sciences, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guohui Zhang, Liang Gao
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
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +2 more sources

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
openaire   +1 more source

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
openaire   +4 more sources

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
openaire   +1 more source

Optimizing Particle Swarm Optimization algorithm

2014 IEEE 27th Canadian Conference on Electrical and Computer Engineering (CCECE), 2014
Particle Swarm Optimization (PSO) algorithm has become more popular recently. It has been shown to be an effective optimization tool in most of the applications. In this paper, we have applied the PSO algorithm to a sample Artificial Neural Network (ANN) application, measured the improvement, and optimized the PSO parameters to improve results as much ...
Iraj Koohi, Voicu Z. Groza
openaire   +1 more source