WASET
	@article{(Open Science Index):https://publications.waset.org/pdf/10011370,
	  title     = {Rule Insertion Technique for Dynamic Cell Structure Neural Network },
	  author    = {Osama Elsarrar and  Marjorie Darrah and  Richard Devin},
	  country	= {},
	  institution	= {},
	  abstract     = {This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.
},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {14},
	  number    = {8},
	  year      = {2020},
	  pages     = {287 - 292},
	  ee        = {https://publications.waset.org/pdf/10011370},
	  url   	= {https://publications.waset.org/vol/164},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 164, 2020},
	}