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But keeping birds away is a difficult proposition: How do you control the behavior of flocks of dozens or hundreds of birds?
The PSO, a population-based heuristic method based on the inspirations of group behavior of flocks of birds to find optimal solution to the non-linear numeric problems.
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The particle swarm optimization (PSO) is one of the most well-known bio-inspired optimization algorithms which mimics movement behavior of animal flocks especially bird and fish flocking.
The proposed approach adopts a swarm intelligence paradigm inspired by the collective behavior of bird flocks.
The PSO algorithm is a population-based search approach, inspired by the behavior of birds' flocks [42] and has shown to be a simple and efficient algorithm compared to other search techniques, including for instance the widespread genetic algorithms [43].
PSO is motivated from the simulation of social behavior of bird flocking.
Particle swarm optimization (PSO) is a stochastic optimization technique developed by the inspiration of the social behavior of bird flocking or fish schooling.
The particle swarm optimization (PSO) algorithm, a relatively recent bio-inspired approach to solve combinatorial optimization problems mimicking the social behavior of birds flocking, is applied to problems of continuum structural topology design for the purpose of investigating optimal topologies and automatically creating innovative solutions.
PSO is a stochastic global optimization technique inspired by social behavior of bird flocking.
But predicting and reliably influencing the behavior of a flock is no simple matter.
PSO is one of the latest evolutionary optimization techniques, inspired by social behavior of bird flocking or fish schooling.
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