Papers Particle Swarm Artificial Life

Computers

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Top: Computers: Artificial_Life: Particle_Swarm: Papers:

• - A paper by Jame Kennedy and William Spears
  
• - In this paper the authors propose a method for adapting the particle swarm optimizer for dynamic environments. The process consists of causing each particle to reset its record of its best position as the environment changes, to avoid making direction
  
• - PSO is used to solve engineering problems with multiple non-linear constraints.
  
• - Application of PSO on reactive power and voltage Control
  
• - PSO is modified to deal with permutation set
  
• - A paper by Yuhui Shi and Russell C. Eberhart.
  
• - A concept for the optimization of nonlinear functions using particle swarm methodology by James Kennedy & Russell Eberhart. This is the first paper talking about PSO.
  
• - A paper by R. Eberhart and X. Hu. PSO is used to train artificial neural network to classify tremor patients from normal subjects.
  
• - 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.
  
• - multiobjective optimization with PSO
  
• - 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.
  
• - a paper by Løvbjerg, M., Rasmussen, T., K. and Krink, T.
  
• - 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.