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- 2014-04-17
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Description:
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 proposed. The relationships between particle
swarm optimization and both artificial life and genetic algorithms are described,
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