Simulate Lightning with Patterns of Cellular Learning Automata and the Model of Particle Swarm Optimization

in this study, we suggest a new model that is made by combination of cellular learning automata (moving) and particle swarm optimization model (binary) to simulate lightning phenomenon. In the proposed model, a population of particles is placed in each cell of the animated cellular learning automata. Learning automata that are independent of the cells, have the duty to regulate the behavior of particles of the cell and enjoy experiences of their own and learning automata of neighboring cells. Simulation results show that this method has better performance than standard models of each of these algorithms. To achieve better results in simulations, steps such as knowing the exact mechanism of lightning, earth behavior against lightning, calculating overvoltage caused by lightning strike and in some cases, simulation of lightning effect by existing software should be considered.

Keywords:

Lightning , Algorithm , Cellular Learning Automata , Particle Swarm Optimization , Simulation