Research Article

An Improved Fuzzy c-Means Clustering Algorithm Based on Shadowed Sets and PSO

Algorithm 1

SP-FCM.
(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 .