Particle swarm optimization (PSO) is a technique for finding approximate solutions to difficult or impossible numeric optimization problems. In particular, PSO can be used to train a neural network.

Particle Swarm Optimization vs. Back-Propagation There are several reasons why you might want to consider using PSO rather than back-propagation to train a neural network. Based on my experience, back ...

An enhanced particle swarm optimization method for wind resistance in high-rise buildings is introduced, focusing on weight ...

Novel 'cuckoo search algorithm' beats particle swarm optimization in engineering design Date: May 28, 2010 Source: Inderscience Summary: The familiar early summer call of the cuckoo has inspired ...

Use of a particle swarm optimization–analytic hierarchy process (PSO-AHP) and a comprehensive fuzzy evaluation of an expert questionnaire shows that these evaluation methods are highly applicable to ...

The increasing use in military and communications applications is expected to provide lucrative opportunities for market ...

Researchers have suggested to use a hybrid version of the so-called salp swarm algorithm ... 94.27% for particle swarm optimization (PSO), 91.63% for standard SSA, 92.70% for the Grey Wolf ...

Evolutionary optimization is more than ant-colony optimization algorithms , bee-colony optimization algorithms (BCO) or particle-swarm optimization (PSO). Swarm intelligence can be applied to ...