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- W4285027679 abstract "This paper has presented a novel concept of a food constraint satisfaction system based on the genetic algorithm (GA) and random walk (RW). The system is a part of the food recommendation system under consideration for recommending proper calorie daily food for obese individuals with overweight. The system estimates the values of overweight, daily needed food calorie (DNC), and saturated DNC (DNCsat) of the individuals from their Body Mass Index (BMI) and Basal Metabolic Rate (BMR) values. The daily food set is the food items for breakfast (BF), lunch (LN), and dinner (DN) selected by an individual. Individuals can choose any food item from the predefined food variables for their daily food set. The overall daily food calorie (ODC) is the total food calories estimated from the daily food set. The system aims to assign only the DNCsat matching food items for the daily food set of each individual from the food list of the system. The system has utilized two random-based algorithms such as GA and RW, to find an appropriate daily food set that satisfies the individual's food choices and DNCsat values. The fitness ratio (FR) of GA and RW’s node evaluation (NDeval) are estimated based on the individuals’ ODC and DNCsat values. The carried-out simulations show that RW outperforms GA in performance and computational complexity. The presented food constraint satisfaction system could effectively satisfy individuals with different food habits and tastes." @default.
- W4285027679 created "2022-07-12" @default.
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- W4285027679 date "2022-07-12" @default.
- W4285027679 modified "2023-09-26" @default.
- W4285027679 title "A Food Constraint Satisfaction System-Based on Genetic and Random Walk Algorithms" @default.
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- W4285027679 doi "https://doi.org/10.1007/978-981-19-2394-4_9" @default.
- W4285027679 hasPublicationYear "2022" @default.
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