Estimating of α-series Process Parameters Using Particle Swarm Optimization Algorithm
Keywords:α-series process, Laplace's test, particle swarm, nonparametric estimation
The α-series stochastic process has special importance in many life areas. In this paper, the particle swarm optimization (PSO) and the least squares (LS) methods are used to estimate parameters of the α-series process. The real data results show that the PSO algorithm is better in estimation compared to the LS method, in term of mean absolute error (MAE).
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