An innovative method for finding out the glycemic index of raw food items based on two layer feed forward neural networks

Abstract

Nowadays, Artificial Neural Networks play a vital role in diverse fields of applications. New researches are evolving in Artificial Neural Networks now and then in the past few decades. Researches in Artificial Neural Networks have grown rapidly over the past few years. This research work deals with an innovative approach for finding out the Glycemic Index of raw food items using two layers feed forward Neural Networks. This is an innovative theoretical idea by which two layer feed forward Neural Networks are imparted training to learn for some known GI values of some of food items called training set. After training, the two layers feed forward Neural Networks system will be used to find out the GI value of new raw food items which were not trained. In this research work, some of the GI values for some raw food items are taken, their contents, amount of nutrients are given as inputs, weight adjustments are given based on their amount of nutrients and the network is trained. After training, the network will be used for finding out GI values of food items which were not trained.