PSO Clustering with Preprocessing of Data Using Artificial Immune System


  •  Ch. Suresh    
  •  E. Vinod kumar    
  •  L.v.v.r.k. Sriharsha    
  •  Suresh Satapathy    
  •  PVGD Reddy    

Abstract

It has been proved by several researchers that particle swarm optimization has shown better results for clustering large datasets. In this paper we present a different approach to that of conventional particle swarm optimization technique. We have used aiNet algorithm of Artificial Immune System(AIS) to preprocess the data i.e. generating the antibodies with more affinity values among different datasets .The obtained result is given to PSO as centroids to get better intra cluster distance compared to that of randomly generated centroids. The comparisons reveal the superiority of AIS over PSO approach for data clustering.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-8989
  • ISSN(Online): 1913-8997
  • Started: 2008
  • Frequency: semiannual

Journal Metrics

WJCI (2022): 0.636

Impact Factor 2022 (by WJCI):  0.419

h-index (January 2024): 43

i10-index (January 2024): 193

h5-index (January 2024): N/A

h5-median(January 2024): N/A

( The data was calculated based on Google Scholar Citations. Click Here to Learn More. )

Contact