@article{(Open Science Index):https://publications.waset.org/pdf/17053,
	  title     = {Particle Swarm Optimization with Interval-valued Genotypes and Its Application to Neuroevolution},
	  author    = {Hidehiko Okada},
	  country	= {},
	  institution	= {},
	  abstract     = {The author proposes an extension of particle swarm optimization (PSO) for solving interval-valued optimization problems and applies the extended PSO to evolutionary training of neural networks (NNs) with interval weights. In the proposed PSO, values in the genotypes are not real numbers but intervals. Experimental results show that interval-valued NNs trained by the proposed method could well approximate hidden target functions despite the fact that no training data was explicitly provided.
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {7},
	  number    = {10},
	  year      = {2013},
	  pages     = {1292 - 1295},
	  ee        = {https://publications.waset.org/pdf/17053},
	  url   	= {https://publications.waset.org/vol/82},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 82, 2013},