@article{(Open Science Index):https://publications.waset.org/pdf/10371,
	  title     = {Ant Colony Optimization for Feature Subset Selection},
	  author    = {Ahmed Al-Ani },
	  country	= {},
	  institution	= {},
	  abstract     = {The Ant Colony Optimization (ACO) is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It has recently attracted a lot of attention and has been successfully applied to a number of different optimization problems. Due to the importance of the feature selection problem and the potential of ACO, this paper presents a novel method that utilizes the ACO algorithm to implement a feature subset search procedure. Initial results obtained using the classification of speech segments are very promising.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {1},
	  number    = {4},
	  year      = {2007},
	  pages     = {999 - 1002},
	  ee        = {https://publications.waset.org/pdf/10371},
	  url   	= {https://publications.waset.org/vol/4},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 4, 2007},
	}