A simplified classification particle swarm optimization algorithm(PSO) is proposed. At first, particles are divided
into three categories, such as the better, ordinary and the worse according to their fitness. Then, three types of simplified
models without velocity part in classical particle swarm optimization algorithm are used to adjust these three kinds of
classified paticles respectively. The diversity of algorithm is enhanced effectively. Through the simulation experiments with
four test functions, compared with the basic PSO and another improved PSO currently, the improved algorithm proposed has
better optimization performance. Finally, the improved algorithm is applied to optimize wind probability modeling, and the
results show that this method has more accuracy and more practical reference than least-squares method.