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A Mathematical AI-Based Diet Analysis and Transformation Model

  • L. K. Gautam
  • S. A. Ladhake
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 732)

Abstract

Inadequacies in nutritional intake can be considered as a major source of adverse effects on the growth and health of individuals in India. A proper balanced diet is essential from the very early stages of life for proper growth, development, to remain active and to reduce the risk of diseases. For those with diabetes, a proper diabetes diet is crucial which depends upon their energy requirements. So a need has been identified to develop educational software which should perform the routine task of analyzing, optimizing, and transforming diet by considering their energy requirements and medical problems. The different nutritional values present in a diet are generally affected by imprecision, which can be represented and analyzed by fuzzy logic. For diet balancing, a metaheuristic local search algorithm is proposed which works in a local search space recording the history of search to make it more effective and optimized. These proposed methods will help users to improve their nutritional intakes by providing detail analysis of their food intake, by providing an optimized diet plan and by suggesting possible changes to make their diet suitable according to their energy requirements.

Keywords

Energy evaluation Fuzzy interval Tabu search Mathematical AI model 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Sipna College of Engineering and TechnologyAmravatiIndia

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