Optimization of training backpropagation algorithm using nguyen widrow for angina ludwig diagnosis

Abstract

Tooth and mouth disease is a common disease, with a prevalence of more than 40% (children aged less than 7 years) in milk teeth and about 85% (adults aged 17 years and over) on permanent teeth. Angina Ludwig is one of mouth disease type that occurs due to infection of the tooth root and trauma of the mouth. 'In this study back propagation algorithm applied to diagnose AnginaLudwig disease (using Nguyen Widrow method in optimization of training time). From the experimental results, it is known that the average BPNN by using Nguyen Widrow is much faster which is about 0.0624 seconds and 0.1019 seconds (without NguyenWidrow). In contrast, for pattern recognition needs, found that back propagation without Nguyen Widrow is much better that is with 90% accuracy (only 70% with NguyenWidrow).