Table 2 The pseudo code of PSO Algorithm... | Emerald Publishing

Table 2

The pseudo code of PSO

Algorithm 1 PSO algorithm to solve the accumulation order in the FGM(1,1) model
Input: the original system behaviors $X^{(0)}$ Output: the optimal values of $r$ Set the maximum number of iterations ${i t e r}_{\max}$
Initialize the particle count N, the dimension D of each particle, the learning factors $c_{1}$ ⁠, $c_{2}$ ⁠,the inertia weight $w_{\min}$ ⁠, $w_{\max}$
Set the initial values for position p and corresponding velocity v
While $k < {i t e r}_{\max}$ do for i = 1: N do Calculate the parameters $\hat{a}$ and $\hat{b}$ by Eq. (4), Evaluate the simulated data by Eq. (6), Compute the value of fitness function by Eq. (7), Update p and v according to: $v_{i j}^{k + 1} = v_{i j}^{k} \times w + c_{i} \times r a n d () \times ({p b e s t}_{i j}^{k} - p_{i j}^{k}) + c_{2} \times r a n d () \times ({g l o b e b e s t}_{j}^{k} - p_{i j}^{k})$ $p_{i j}^{k} = v_{i j}^{k + 1} + p_{i j}^{k}, w = w_{\max} - \frac{w_{\max} - w_{\min}}{{i t e r}_{\max}} \times k$ End for $k = k + 1 .$
End while
Return the optimal values of $r$

Algorithm 1 PSO algorithm to solve the accumulation order in the FGM(1,1) model
Input: the original system behaviors $X^{(0)}$ Output: the optimal values of $r$ Set the maximum number of iterations ${i t e r}_{\max}$
Initialize the particle count N, the dimension D of each particle, the learning factors $c_{1}$ , $c_{2}$ ,the inertia weight $w_{\min}$ , $w_{\max}$
Set the initial values for position p and corresponding velocity v
While $k < {i t e r}_{\max}$ do for i = 1: N do Calculate the parameters $\hat{a}$ and $\hat{b}$ by Eq. (4), Evaluate the simulated data by Eq. (6), Compute the value of fitness function by Eq. (7), Update p and v according to: $v_{i j}^{k + 1} = v_{i j}^{k} \times w + c_{i} \times r a n d () \times ({p b e s t}_{i j}^{k} - p_{i j}^{k}) + c_{2} \times r a n d () \times ({g l o b e b e s t}_{j}^{k} - p_{i j}^{k})$ $p_{i j}^{k} = v_{i j}^{k + 1} + p_{i j}^{k}, w = w_{\max} - \frac{w_{\max} - w_{\min}}{{i t e r}_{\max}} \times k$ End for $k = k + 1 .$
End while
Return the optimal values of $r$

Source(s): Author’s own creation