A concept for the optimization of nonlinear functions using particle swarm methodology by James Kennedy and Russell Eberhart. This is the first paper talking about PSO.
A paper by Frans van den Bergh and Andries P. Engelbrecht, South Africa. The interesting point is that they split the input vectors to several sub-vectors, each which is optimized cooperatively in its own swarm.
A hybrid PSO is proposed by introduction of the natural selection mechanism. The authors demonstrated hybrid PSO is better than original version on distribution state estimation problems.
PSO is used to adjust the network weights, with the Adaptive Neural Swarming method, the controller could adapt to environmental changes. It is tested in a real-world task of controlling a simulated non-linear bioreactor.
