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Application of Imperialist Competitive Algorithm for Feature Selection: A Case Study on Bulk Rice Classification

International Journal of Computer Applications
© 2012 by IJCA Journal
Volume 40 - Number 16
Year of Publication: 2012
S. J. MousaviRad
F. Akhlaghian Tab
K. Mollazade

S J MousaviRad, Akhlaghian F Tab and K Mollazade. Article: Application of Imperialist Competitive Algorithm for Feature Selection: A Case Study on Bulk Rice Classification. International Journal of Computer Applications 40(16):41-48, February 2012. Full text available. BibTeX

	author = {S. J. MousaviRad and F. Akhlaghian Tab and K. Mollazade},
	title = {Article: Application of Imperialist Competitive Algorithm for Feature Selection: A Case Study on Bulk Rice Classification},
	journal = {International Journal of Computer Applications},
	year = {2012},
	volume = {40},
	number = {16},
	pages = {41-48},
	month = {February},
	note = {Full text available}


Feature selection plays an important role in pattern recognition. The better selection of a feature set usually results the better performance in a classification problem. This work tries to select the best feature set for classification of rice varieties based on image of bulk samples using imperialist competition algorithm. Imperialist competition algorithm is a new evolutionary optimization method that is inspired by imperialist competition. Results showed the feature set selected by the imperialist competition algorithm provide the better classification performance compared to that obtained by genetic algorithm technique


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