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A novel artificial intelligence method for weekly dietary menu planning.

机译:每周饮食菜单计划的一种新颖的人工智能方法。

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OBJECTIVES: Menu planning is an important part of personalized lifestyle counseling. The paper describes the results of an automated menu generator (MenuGene) of the web-based lifestyle counseling system Cordelia that provides personalized advice to prevent cardiovascular diseases. METHODS: The menu generator uses genetic algorithms to prepare weekly menus for web users. The objectives are derived from personal medical data collected via forms in Cordelia, combined with general nutritional guidelines. The weekly menu is modeled as a multilevel structure. RESULTS: Results show that the genetic algorithm-based method succeeds in planning dietary menus that satisfy strict numerical constraints on every nutritional level (meal, daily basis, weekly basis). The rule-based assessment proved capable of manipulating the mean occurrence of the nutritional components thus providing a method for adjusting the variety and harmony of the menu plans. CONCLUSIONS: By splitting the problem into well determined sub-problems, weekly menu plans that satisfy nutritional constraints and have well assorted components can be generated with the same method that is for daily and meal plan generation.
机译:目标:菜单计划是个性化生活方式咨询的重要组成部分。本文介绍了基于网络的生活方式咨询系统Cordelia的自动菜单生成器(MenuGene)的结果,该系统提供个性化建议以预防心血管疾病。方法:菜单生成器使用遗传算法为网络用户准备每周菜单。目的来自通过Cordelia中的表格收集的个人医疗数据,以及一般的营养指南。每周菜单被建模为多层结构。结果:结果表明,基于遗传算法的方法成功地计划了满足每个营养水平(餐,日,周,周)严格的数值限制的饮食菜单。事实证明,基于规则的评估能够操纵营养成分的平均发生,从而提供了一种调整菜单计划的多样性和和谐性的方法。结论:通过将问题分解为确定的子问题,可以使用与生成每日计划和膳食计划相同的方法来生成满足营养限制并且成分齐全的每周菜单计划。

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