Particle Swarm Optimization
Another "best" value that is tracked by the particle swarm optimizer is the best value, obtained so far by any particle in the neighbors of the particle. The particle swarm optimization concept consists of, at each time step, changing the velocity of (accelerating) each particle
Repulsive particle swarm optimization
Wikipedia: In mathematics, specifically in optimization, repulsive particle swarm optimization (RPSO) is a global optimization algorithm. It belongs to the class of stochastic evolutionary global optimizers, and is a variant of particle swarm optimization (PSO).
Particle Swarm Optimization: Bibliography
Fan, H.-Y. and Shi, Y. Study on Vmax of particle swarm optimization. Proceedings of the Workshop on Particle Swarm Optimization 2001, Indianapolis, IN. Fourie, P. C. and Groenwold, A. A. Particle swarms in topology optimization. Kennedy, J. Out of the computer, into the world: externalizing the particle swarm.
Particle Swarm Optimization
The neural-net application described in Section 3.4, for instance, showed that the particle swarm optimizer could train NN weights as effectively as the usual error backpropagation method. The particle swarm optimizer has also been used to train a neural network to classify the Fisher Iris Data Set [3].
Project Computing - PSO Visualisation
The bottom of this page contains a simple Java applet which visually demonstrates a particle swarm searching for a maximum value in a 3-D landscape. A brief introduction to Particle Swarm Optimization.
Special Issue on Particle Swarm Optimisation
This journal special issue solicits novel high-quality scientific contributions on Particle Swarm Optimization. Please, select 'Special Issue on Particle Swarm Optimization' as the article type. Authors are invited to submit original work on topics relevant for this special issue. The submission deadline is June 1, 2008.
CiteSeerX — Matching algorithms to problems: An experimental test of the particle swarm and some genetic...
The Particle Swarm: Social Adaptation of Knowledge – Kennedy - 1997. A discrete binary version of the particle swarm algorithm – Kennedy, Eberhart - 1997. Matching algorithms to problems: An experimental test of the particle swarm and some genetic algorithms on the multimodal problem generator (1998) [25 citations — 0 self]
Cooperative Learning in Neural Networks using Particle Swarm Optimizers - CiteSeerX
Particle swarm optimization – Kennedy, Eberhart - 1995. A new optimizer using particle swarm theory – Eberhart, Kennedy - 1995. Comparing inertia weights and constriction factors in particle swarm optimization – Eberhart, Shi - 2000.
pso
Think Locally, Act Locally: A Framework for Adaptive Particle Swarm Optimizers. In Particle Swarm Optimization, each particle moves in the search space and updates its velocity according to best previous positions already found by its neighbors (and itself), trying to find an even better position.
Particle Swarm Optimization In Electromagnetics (Synthesis Lectures on Computational Electromagnetic-Sciences-DuAn
Particle Swarm Optimization In Electromagnetics (Synthesis Lectures on Computational Electromagnetics) Particle Swarm Optimization In Electromagnetics (Synthesis Lectures on Computational Electromagnetic
Particle Swarm People
I have recently started working on the eXtended Particle Swarm XPS optimisation project (2004-10). PSO papers: "Understanding particle swarm optimisation by evolving problem landscapes", "Extending particle swarm optimisation via genetic programming" People, working or having worked on Particle Swarm.
Explore by Category
Theoretical Computer Science
Elsevier Scientific Journals
Artificial Intelligence, Theoretical Computer Science, Neuron, Intelligence
Computer Science Journals
Artificial Intelligence, Machine Learning, Computer, Lecture Notes in Computer Science, Computational Linguistics, Theoretical Computer Science
Mathematical Terminology
Neural Networks
Neural network, Perceptron, Backpropagation, Neural Information Processing Systems
Optimization Algorithms
Control Theory
Computational Neuroscience
Neural network, Connectionism, Neural Information Processing Systems
Mathematical Optimization
Constraint, Linear programming, Optimal control, NP-complete, Genetic programming, Optimization