Использование иммунного и генетического алгоритмов для оптимизации обучения нейронной сети

Abstract

Nowadays, computer technologies are widely implemented and used in all areas of human activity, including in medicine. They can significantly improve the quality of healthcare by modeling a pathological process in a particular disease. A neural network can be trained to determine diseases, but training may take a long time because of the large number of indicators of human health, as well as increased demands on the accuracy of recognition. Training time can be reduced by using optimization algorithms presented in this article.