Metaheuristics Optimization Algorithm to an Optimal Moroccan Diet

Moutaouakil, Karim El; Cheggour, Mouna; Chellak, Saliha; Hicham, Baïzri

doi:10.1109/icnisc54316.2021.00072

Cited by 11 publications

(12 citation statements)

References 18 publications

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“…To solve the optimal Morocco diet problem, we have proposed, recently, an approach based on a quadratic optimization programming (P ) that permit to minimize the total glycemic load and unfavorable nutrients gaps [2]:…”

Section: Optimal Morocco Diet Modelingmentioning

confidence: 99%

“…To minimize the cost function we can utilize a recurrent network [18][19][20]. We can also use evolutionary heuristic methods such as: firefly optimization [21], genetic algorithm [23], particle swarm algorithm, stochastic fractal search with specific operators [2], etc. In our case, we employ the fuzzy genetic algorithm to take advantage of the evolutionary approaches to generating highquality decisions and the capacity of fuzzy logic to operate in stochastic environments.…”

Section: Nutrients Crisp Representation Using Optimal Auto-encodermentioning

confidence: 99%

“…Most of the solutions to the optimal regime problem are based on mathematical modeling implementing nonlinear optimization models with constraints [1][2][3][4][5]. The different components of these models are the translation of knowledge and recommendations of experts in the field of nutrition [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

“…We propose, in this work, an original intelligent system, implementing our mathematical model [2], allowing to draw up a personalized optimal diet based on optimal deep learning neural network that predict the individual dailly nutrients requirements. Three types of representations of daily needs are used: nominal representation [10] and [11], interval representation [12], and exhaustive representation [13].…”

Section: Introductionmentioning

confidence: 99%

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Optimal fuzzy deep daily nutrients requirements representation: Application to optimal Morocco diet problem

Moutaouakil¹,

Chellak²,

Hicham³

2022

Math. Model. Comput.

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Solving the optimal diet problem necessarily involves estimating the daily requirements in positive and negative nutrients. Most approaches proposed in the literature are based on standard nominal estimates, which may cause shortages in some nutrients and overdoses in others. The approach proposed in this paper consists in personalizing these needs based on an intelligent system. In the beginning, we present the needs derived from the recommendations of experts in the field of nutrition in trapezoidal numbers. Based on this model, we generate a vast database. The latter is used to educate a deep learning neural network, the architecture of which we optimize by the fuzzy genetic algorithm method in the way of adopting a customized regulation term. Our system estimates nutrient requirements based only on gender and age. These estimations are integrated into a mathematical model obtained in our previous work. Then we again use the fuzzy genetic algorithm to draw up personalized diets. The proposed system has demonstrated a very high capacity to predict the needs of different individuals and has allowed the drawing up of very high-quality diets.

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Section: Optimal Morocco Diet Modelingmentioning

confidence: 99%

Section: Nutrients Crisp Representation Using Optimal Auto-encodermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimal fuzzy deep daily nutrients requirements representation: Application to optimal Morocco diet problem

Moutaouakil¹,

Chellak²,

Hicham³

2022

Math. Model. Comput.

Self Cite

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“…For healthy individuals, balanced diets reduce the likelihood of developing chronic diseases; whereas for individuals with chronic diseases, balanced diets reduce the likelihood of entering dangerous stages, especially for diabetics, cardiovascular disease, obesity and cancer [1][2][3][4][5][6]. It is a matter of satisfying the body's demands in an optimal manner.…”

Section: Introductionmentioning

confidence: 99%

Intelligent Local Search Optimization Methods to Optimal Morocco Regime

Moutaouakil¹,

Chellak²,

Hicham³

et al. 2023

Artificial Intelligence

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In this paper, we compare three well-known swarm algorithms on optimal regime based on our mathematical optimization model introduced recently. Different parameters of this latter are estimated based on 176 foods and on who’s the nutrients values are calculated for 100 g. The daily nutrients needs are estimated based on the expert’s knowledge. Different experimentations are realized for different configurations of the considered swarm algorithms. Compared to Stochastic Fractal Search (SFS) and Particle Swarm Optimization Algorithm (PSO), the Firefly Algorithm (FA) produces the main suitable regimes.

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