An Intelligent Artificial Neural Network and Fuzzy Logic-Based Diet Advisory System

The goal of the present study was to develop an automatic and high-performance professional nutrition and diet advisor system to help the users to evaluate their nutrition conditions and get useful nutritional information. The study also aimed to provide users with a healthy meal plan based on their physical conditions such as weight, height, age, etc.
This study was an applied research towards developing an intelligent diet advisor system. We focused on fuzzy logic and artificial neural networks as the means of implementation. The dataset was collected from one thousand patients’ files chosen randomly from the files of the patients referred to a diet clinic in Isfahan City, Iran, between 2011 and 2015. The collected data were entered into excel software during four months of study.
The designed three-layered artificial neural system with back propagation algorithm was able to diagnose the best dietary plan among the eleven proposed plans. The designed neural networks were able to work with 92% of accuracy, while the proposed fuzzy logic-based system carried out the procedure with 97% of accuracy.
The results of this research indicated that this dietary proposal system using neural networks and the fuzzy logic was sufficient enough to be used to propose appropriate diet and meal plans to individuals. As a result, it could allow the users to receive the very efficient diet plans after entering their personal information easily, accurately, and almost free of charge.