@article{(Open Science Index):https://publications.waset.org/pdf/8531,
	  title     = {Exponential Particle Swarm Optimization Approach for Improving Data Clustering},
	  author    = {Neveen I. Ghali and  Nahed El-Dessouki and  Mervat A. N. and  Lamiaa Bakrawi},
	  country	= {},
	  institution	= {},
	  abstract     = {In this paper we use exponential particle swarm
optimization (EPSO) to cluster data. Then we compare between
(EPSO) clustering algorithm which depends on exponential variation
for the inertia weight and particle swarm optimization (PSO)
clustering algorithm which depends on linear inertia weight. This
comparison is evaluated on five data sets. The experimental results
show that EPSO clustering algorithm increases the possibility to find
the optimal positions as it decrease the number of failure. Also show
that (EPSO) clustering algorithm has a smaller quantization error
than (PSO) clustering algorithm, i.e. (EPSO) clustering algorithm
more accurate than (PSO) clustering algorithm.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {2},
	  number    = {6},
	  year      = {2008},
	  pages     = {1818 - 1822},
	  ee        = {https://publications.waset.org/pdf/8531},
	  url   	= {https://publications.waset.org/vol/18},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 18, 2008},