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