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Reseach Article

Classification of Data by Hybrid Particle Swarm Optimization and Gravitational Search Algorithm

by Vijita Nair, Kavita Barse, Vivek Kumar
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 179 - Number 42
Year of Publication: 2018
Authors: Vijita Nair, Kavita Barse, Vivek Kumar
10.5120/ijca2018917003

Vijita Nair, Kavita Barse, Vivek Kumar . Classification of Data by Hybrid Particle Swarm Optimization and Gravitational Search Algorithm. International Journal of Computer Applications. 179, 42 ( May 2018), 34-38. DOI=10.5120/ijca2018917003

@article{ 10.5120/ijca2018917003,
author = { Vijita Nair, Kavita Barse, Vivek Kumar },
title = { Classification of Data by Hybrid Particle Swarm Optimization and Gravitational Search Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { May 2018 },
volume = { 179 },
number = { 42 },
month = { May },
year = { 2018 },
issn = { 0975-8887 },
pages = { 34-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume179/number42/29365-2018917003/ },
doi = { 10.5120/ijca2018917003 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:58:11.251378+05:30
%A Vijita Nair
%A Kavita Barse
%A Vivek Kumar
%T Classification of Data by Hybrid Particle Swarm Optimization and Gravitational Search Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 179
%N 42
%P 34-38
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The problem of classification is may be one of the greatest colossally considered in the data mining and in intelligent retrieval system. The classifications tasks have been studied by researchers from several domains from decades. . PSOGSA based data classification can also be apply, might yield more efficient and promising results , in proposed work which, possesses classification of standard data using gravitational search algorithm with optimize manner .So classification of data done by the famous widely used method Feed forward neural network with gravitational search algorithm Particle swarm optimization is a popular heuristic algorithm that had been applied on many optimization problems over the years including data classification problem This modified PSO is combined with gravitational search algorithm to solve its slow Execution time in the last iterations, making the hybrid PSOGSA algorithm

References
  1. Charu C. Agrawal, “Data Classification: Algorithms and Applications”, CRC Press, Taylor and Francis Group.2014.
  2. Pheyedali Miraajalili, Siti Kaiton Mohd Washim, "A New Hybrid FNN-GSA Algorithm for Function Optimization", IEEE, International Conference on Computer and Information Application (ICCIA 2013)
  3. Wenzhong Shi, Kimfung Liu, Hua Zhang, “A study of supervised classification accuracy in fuzzy topological methods,” International Journal of Applied Earth Observation and Geo information, vol.13,pp. 89-99,2011.
  4. Dean, Jeffrey, and Sanjay Ghemawat. "Map Reduce: a flexible data processing tool." Communications of the ACM 53.1, pp. 72-77, 2010.
  5. Yu, Lean, et al. "Evolving least squares support vector machines for stock market trend mining." IEEE Transactions on evolutionary computation 13.1, pp. 87-102, 2009.
  6. C. Aggarwal. “Data Streams: Models and Algorithms”, Springer, vol. 31, 2007.
  7. H. Peng, F. Long, and C. Ding. “Feature selection based on mutual information: Criteria of max dependency, max-relevance, and min-redundancy”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 27(8), pp. 1226–1238, 2005.
  8. N. V. Chawla, N. Japkowicz, and A. Kotcz. Editorial: Special Issue on Learning from Imbalanced, pp 1-6, 2004.
  9. N. V. Chawla, N,” Data Sets”, ACM SIGKDD Explorations Newsletter, 6(1):1–6, 2004.
  10. R. Duda, P. Hart, and D. Stork, “Pattern Classification” Wiley, pp 20- 25, 2001.
  11. Kludack Ruggerie, Aleix M. MartõÂnez, and Avinash C. Kak, “PCA versus LDA”, IEEE, 2001.
Index Terms

Computer Science
Information Sciences

Keywords

Gravitational search algorithm Particle swarm optimization