Feature Selection for Cotton Foreign Fiber Objects Based on PSO Algorithm

Abstract : Due to large amount of calculation and slow speed of the feature selection for cotton fiber, a fast feature selection algorithm based on PSO was developed. It is searched by particle swarm optimization algorithm. Though search features by using PSO, it is reduced the number of classifier training and reduced the computational complexity. Experimental results indicate that, in the case of no loss of the classification performances, the method accelerates feature selection.
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Communication dans un congrès
Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-370 (Part III), pp.446-452, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27275-2_50〉
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Hengbin Li, Jinxing Wang, Wenzhu Yang, Shuangxi Liu, Zhenbo Li, et al.. Feature Selection for Cotton Foreign Fiber Objects Based on PSO Algorithm. Daoliang Li; Yingyi Chen. 5th Computer and Computing Technologies in Agriculture (CCTA), Oct 2011, Beijing, China. Springer, IFIP Advances in Information and Communication Technology, AICT-370 (Part III), pp.446-452, 2012, Computer and Computing Technologies in Agriculture V. 〈10.1007/978-3-642-27275-2_50〉. 〈hal-01361171〉

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