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Automatic Diet Generation by Artificial Bee Colony Algorithm

机译:自动饮食由人造蜂菌落算法产生

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The overweight in the population has become a problem due to the deficiency on the nutritional contributions, increasing the number of people with diseases. The origin of this problem lies in the way people eat, with a poor nutritional quality and in excessive quantities. To solve this, it is necessary that people consider balance diets with the nutritional expectation and the necessary food to improve people's health and reduce the rates of overweight and obesity. The diet design can be stated as an optimization problem and solved using different, algorithms. In this paper, an Artificial Bee Colony (ABC) algorithm has been proposed to automatically design diets considering the physical characteristics of the subjects to find the best diet that satisfies their nutritional requirements using the USDA National Nutrient Database. Particularly, this research is focused on relatively healthy people between 18 and 55 years old to help them to avoid nutritional related diseases. The proposed methodology is compared against particle swarm optimization using the Harris-Benedict equation in order to verify if is capable to achieve the calorie goal.
机译:由于营养贡献的不足,人口的超重已成为一个问题,增加了疾病的人数。这个问题的起源在于人们吃的方式,营养质量差和过量数量。为了解决这一问题,人们必须考虑与营养期望和必要的食物进行平衡饮食,以改善人们的健康,减少超重和肥胖的率。饮食设计可以表示为优化问题,并使用不同的算法解决。在本文中,已经提出了一种人造群菌落(ABC)算法,以便在考虑受试者的物理特征来找到最佳饮食,以找到满足他们使用美国农业部国家营养数据库的营养需求的最佳饮食。特别是,这项研究专注于18至55岁之间的相对健康的人,以帮助他们避免营养相关疾病。使用Harris-Benedict方程将所提出的方法与粒子群优化进行比较,以验证是否能够实现卡路里的目标。

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