Models, Methods and Tools of Planning Human Diet

Abstract

In this article was taken to consideration an issue of planning a person's diet and nutrition and were determined factors that significantly affect the choice of food. It was covered approaches studies on the basis of which modern systems of recommendations for a balanced diet work. A classification of decision support systems regarding the choice of diet and diet is provided based on the data on the basis of which they provide recommendations. The limitations of the linear combination of the user's choice factors and the elements characterizing his profile are shown when modeling a large number of hidden factors affecting the user's diet. The main focus of the research is directed to the analysis of models and methods used in the development of intelligent systems decision support systems about balanced nutrition. The analysis of the advantages and disadvantages of intelligent recommendation systems showed the relevance of developing a complete system that can provide recommendations taking into account a large number of explicit and implicit factors affecting the user's diet and nutrition on his health. Based on the analysis of the models and methods of artificial intelligence already used in such systems, the perspective of the development of models and methods of machine learning has been substantiated and the field of interest for further research has been formed. These studies are planned to be addressed to the construction of a multilayer system of deep machine learning, which will be able to take into account a large number of factors that depend on a balanced diet and healthy eating of each user.