Intelligent Local Search for an Optimal Control of Diabetic Population Dynamics

被引：9
作者：
Abdellatif E.O. [1 ]
Karim E.M. [1 ]
Hicham B. [2 ]
Saliha C. [3 ]
机构：
[1] Engineering Science Laboratory (LSI), Polydisplinary Faculty of Taza, USMBA, Fez
[2] The Biosciences and Health laboratory, Faculty of Medicine and Pharmacy, Cadi Ayyad University, Marrakech
[3] MorphoSciences Research Laboratory, Faculty of Medicine and Pharmacy, Cadi Ayyad University, Marrakech
来源：
Mathematical Models and Computer Simulations | 2022年 / 14卷 / 6期
关键词：
artificial intelligence; diabetes; dynamic system; optimal control;
D O I：
10.1134/S2070048222060047
中图分类号：
学科分类号：
摘要：
Abstract: Diabetes is a chronic disease that affects millions of people in the world. This work has two objectives: (a) elaboration of a state of the art on the different dynamic systems with economic function proposed in the literature controlling diabetes in order to alleviate the socio-economic damage caused by it; (b) implementation of the best performing local search artificial intelligence methods (metaheuristics) to solve the kernel model dealing with the common compartments between all these models. The idea behind the use of metaheuristics is that these intelligent methods are able to provide an excellent approximation of a very economical control marked by its continuity and which does not completely exhaust the human and material resources programmed for the control of the studied phenomenon. Our work is marked by a richness of experiments allowing to analyze several interesting aspects of the phenomenon: quality of the control, cost of the control, and behavior of the different compartments in the presence of the control. In comparison with bees algorithm (BA), firefly algorithm (FA), particle swarm algorithm (PSO), genetic algorithm (GA), moth swarm algorithm (MSA), stochastic fractal search (SFS), wind driven optimization (WDO), and probabilistic bees algorithm (PBA). The stochastic fractal search (SFS) method has shown an unprecedented ability to produce continuous, economical controls capable of alleviating socio-economic damage against a reasonable budget. © 2022, Pleiades Publishing, Ltd.
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收藏
页码：1051 / 1071
页数：20
相关论文
共 40 条
[31]  
Medvedeva M., Simos T.E., Tsitouras C., Katsikis V., Direct estimation of SIR model parameters through second-order finite differences, Math. Methods Appl. Sci., 44, pp. 3819-3826, (2021)
[32]  
Ding F., Combined state and least squares parameter estimation algorithms for dynamic systems, Appl. Math. Modell., 38, pp. 403-412, (2014)
[33]  
El Ouissari A., El Moutaouakil K., Density based fuzzy support vector machine: application to diabetes dataset, Math. Model. Comput., 8, pp. 747-760, (2021)
[34]  
Aharrane N., Dahmouni A., El Moutaouakil K., Satori K., A robust statistical set of features for Amazigh handwritten characters, Pattern Recognit. Image Anal., 27, pp. 41-52, (2017)
[35]  
Bas E., A robust optimization approach to diet problem with overall glycemic load as objective function, Appl. Math. Modell., 38, pp. 4926-4940, (2014)
[36]  
Lind T., Lonnerdal B., Stenlund H., Ismail D., Seswandhana R., Ekstrom E.-C., Persson L.-A., A community-based randomized controlled trial of iron and zinc supplementation in Indonesian infants: interactions between iron and zinc, Am. J. Clin. Nutr., 77, pp. 883-890, (2003)
[37]  
Specker B.L., Beck A., Kalkwarf H., Ho M., Randomized trial of varying mineral intake on total body bone mineral accretion during the first year of life, Pediatrics, 99, (1997)
[38]  
Donati M., Menozzi D., Zighetti C., Rosi A., Zinetti A., Scazzina F., Towards a sustainable diet combining economic, environmental and nutritional objectives, Appetite, 106, pp. 48-57, (2016)
[39]  
El Moutaouakil K., Cheggour M., Chellak S., Baizri H., Metaheuristics optimization algorithm to an optimal Moroccan diet, In Proc. 2021 7Th Annual International Conference on Network and Information Systems for Computers (ICNISC 2021), pp. 364-369, (2021)
[40]  
You A., Dietary Guidelines for Americans
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