@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}, }