K. E. El Moutaouakil, A. Ahourag, Fatima Belhabib, Aayah Hammoumi, A. Patriciu, S. Chellak, Hicham Baizri
{"title":"Fuzzy Modeling to Personalized Nutritional Menu","authors":"K. E. El Moutaouakil, A. Ahourag, Fatima Belhabib, Aayah Hammoumi, A. Patriciu, S. Chellak, Hicham Baizri","doi":"10.2174/0115734013293555240319070046","DOIUrl":null,"url":null,"abstract":"\n\nWhile most healthy diets can help control the progression of disease,\nthey can fail in the long term for many factors. Patients abandon the diet altogether after a\nwhile because it is too restrictive or the foods are unappealing; still, others engage in less physical\nactivity because they consume fewer calories. What's more, almost all plans are based on\noptimization models. These models produce statistical diets offering limited choices to users,\nand a small substitution can call the whole diet into question.\n\n\n\nAlmost all plans are based on optimization models. These models produce statistical diets offering limited choices to users, and a small substitution can call the whole diet into question.\n\n\n\nThis article develops an intelligent system for generating flexible nutritional menus\nthat each person can adopt to their environment and dietary preferences (food availability,\nprice, patient eating habits, etc.). The system implements mathematical fuzzy optimization\nmodels and constraint satisfaction programming.\n\n\n\nObjective: this paper builds a personalized nutritional menu based on mathematical modeling and constraints satisfaction programming.\n\n\n\nFirst, the Moroccon foods were decomposed using fuzzy Cmeans.\nNext, the artificial foods, formed by the centers, were introduced into a fuzzy mathematical optimization\ndiet model, which controlled the total glycemic load and met the World Health Organization\n(WHO) and Dietary Guidelines for Americans (GDA) recommendations (requirements\nfor personalized menu). Then, we used a genetic algorithm strategy to generate optimal\nserving sizes and to build a nutritional menu based on the groups formed. To help patients\nchoose customized diets, the menu was transformed into a constraint satisfaction programming\nmodel.\n\n\n\nThe proposed strategy was applied to Moroccan foods, experimental results show that\nall diets offer a wide range of choices to users and that substitutions comply with WHO and\nGDA recommendations.\n\n\n\nThe suggested scheme has been applied to Moroccan foods; experimental findings\ndemonstrate that all diets provide users with a wide variety of options that keeps consumers\non their diet.\n","PeriodicalId":502426,"journal":{"name":"Current Nutrition & Food Science","volume":" 34","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Nutrition & Food Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/0115734013293555240319070046","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
While most healthy diets can help control the progression of disease,
they can fail in the long term for many factors. Patients abandon the diet altogether after a
while because it is too restrictive or the foods are unappealing; still, others engage in less physical
activity because they consume fewer calories. What's more, almost all plans are based on
optimization models. These models produce statistical diets offering limited choices to users,
and a small substitution can call the whole diet into question.
Almost all plans are based on optimization models. These models produce statistical diets offering limited choices to users, and a small substitution can call the whole diet into question.
This article develops an intelligent system for generating flexible nutritional menus
that each person can adopt to their environment and dietary preferences (food availability,
price, patient eating habits, etc.). The system implements mathematical fuzzy optimization
models and constraint satisfaction programming.
Objective: this paper builds a personalized nutritional menu based on mathematical modeling and constraints satisfaction programming.
First, the Moroccon foods were decomposed using fuzzy Cmeans.
Next, the artificial foods, formed by the centers, were introduced into a fuzzy mathematical optimization
diet model, which controlled the total glycemic load and met the World Health Organization
(WHO) and Dietary Guidelines for Americans (GDA) recommendations (requirements
for personalized menu). Then, we used a genetic algorithm strategy to generate optimal
serving sizes and to build a nutritional menu based on the groups formed. To help patients
choose customized diets, the menu was transformed into a constraint satisfaction programming
model.
The proposed strategy was applied to Moroccan foods, experimental results show that
all diets offer a wide range of choices to users and that substitutions comply with WHO and
GDA recommendations.
The suggested scheme has been applied to Moroccan foods; experimental findings
demonstrate that all diets provide users with a wide variety of options that keeps consumers
on their diet.