Title :
Parameters estimation for nonlinear moving average model using Supernova metaheuristic
Author :
Delgado, Eddy Mesa ; Cogollo, Myladis R. ; Velásquez, Juan David
Author_Institution :
Fac. de Minas, Univ. Nac. de Colombia, Medellín, Colombia
Abstract :
In the practice, to find the parameters for nonlinear Moving average(NLMA) models is difficult because there are not analytical way to solve maximum likelihood function. In this paper, we compare the parameters estimated for NLMA model with Supernova and PSO-DE algorithm. We found that Supernova estimation is better in terms of a reduction of error and nearest solutions to optimal point.
Keywords :
evolutionary computation; maximum likelihood estimation; moving average processes; particle swarm optimisation; NLMA models; PSO-DE algorithm; maximum likelihood function; nonlinear moving average model; parameters estimation; supernova metaheuristic; Computational modeling; Educational institutions; Electric shock; Maximum likelihood estimation; Silicon compounds; Time series analysis; Vectors; Metaheuristics; Supernova; intelligent systems; moving average; optimization;
Conference_Titel :
Computing Congress (CCC), 2012 7th Colombian
Conference_Location :
Medellin
Print_ISBN :
978-1-4673-1475-6
DOI :
10.1109/ColombianCC.2012.6398019
