(1) Initialize and , let , the real number , iteration counter , iteration counter , maximum |
iteration number of PSO. |
(2) Initialize the population size , the initial velocity of particles, the initial position of particles, , , , the threshold |
and attrition rate . |
(3) DO { |
Repeat { |
(a) Update partition matrix for all particles by (3). |
(b) Calculate the cluster center for each particle by (4). |
(c) Calculate the fitness value for each particle by (7). |
(d) Calculate for each particle. |
(e) Calculate for the swarm. |
(f) Update the velocity and position of each particle by (5). |
(g) |
} |
Until PSO termination condition is met |
(i) Calculate the optimal threshold for each column of partition matrix by (12), |
and relocate of th cluster according to |
(ii) Calculate cardinality for each cluster on the basis of the number of data whose membership value equal to 1 by (14), |
|
(iii) Remove all clusters whose and is among lowest cardinality |
(iv) Update cluster number C |
(v) Calculate cluster validity index by (13) |
(vi) Update iteration counter |
} |
While termination condition is not met |
The termination condition of PSO in this method is (reach the maximum number of iterations) or the velocity |
updates are close to zero over a number of iterations. |
The algorithm can terminate under either of the following two conditions: |
(1) The prototype parameters in stabilize within some threshold . |
(2) The number of clusters has reached the minimum limit . |