Research Article
A Feature Weighted Fuzzy Clustering Algorithm Based on Multistrategy Grey Wolf Optimization
| (1) | set the parameters | | (2) | generate N individuals as initial population in search space according to algorithm 1 | | (3) | calculate the fitness value of each wolf | | (4) | determine the values of Xα, Xβ, and Xδ and let t = 0 | | (5) | while t < tmax | | (6) | for i = 1 to N | | (7) | update the position of the ith grey wolf according to equations (11)–(13) | | (8) | end for | | (9) | implement the GOBL strategy for all individuals in the current population to update the position of each individual | | (10) | calculate the fitness value of each wolf | | (11) | update and save Xα, Xβ, and Xδ | | (12) | calculate the value of convergence factor a according to equation (14), and then, calculate the values of A and C according to equations (9) and (10) | | (13) | t = t+1 | | (14) | end while | | (15) | return Xa |
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