Multistep Wind Speed Forecasting Using a Novel Model Hybridizing Singular Spectrum Analysis, Modified Intelligent Optimization, and Rolling Elman Neural Network

Algorithm 2

PSO.

Parameters:

—the number of particles.

—the maximum number of iterations.

—the parameters of PSO.

(1) Set the parameters of PSO.

(2) Generate initial population of particles randomly.

(3) FOR EACH  :   DO

(4) ;

(5) ;

(6) END FOR

(7) Find the best value of particles.

(8) WHILE    DO

(9) Find the best fitness value for each candidates.

(10) FOR EACH  :   DO

(11) Calculate each particle fitness function.

(12) IF    THEN

(13)

(14) END IF

(15) END FOR

(16) Choose the candidate with the best fitness value of all the candidates

(17) FOR EACH :   DO

(18) IF    THEN

(19)

(20)

(21) END IF

(22) END FOR

(23) Update the values of all the candidates by using PSO’s evolution equations.

(24) FOR EACH :    DO

(25)

(26)

(27) END FOR

(28) END WHILE