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10.1177/1460458220976719 http://scihub22266oqcxt.onion/10.1177/1460458220976719 33438501!ä!33438501 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Health+Informatics+J 2021 ; 27 (1): 1460458220976719 Nephropedia Template TP {{tp|p=33438501|t=2021. Recommending healthy meal plans by optimising nature-inspired many-objective diet problem |pdf=|usr=}}{{33438501}} gab.com Text Recommending healthy meal plans by optimising nature-inspired many-objective diet problem JO: Health Informatics J http://www.kidney.de/pget.php?&tw=1&pmid=33438501 #FOAvip Healthy eating is an important issue affecting a large part of the world population, so human diets are becoming increasingly popular, especially with the devastating consequences of Coronavirus Disease (Covid-19). A realistic and sustainable diet plan can help us to have a healthy eating habit since it considers most of the expectations from a diet without any restriction. In this study, the classical diet problem has been extended in terms of modelling, data sets and solution approach. Inspired by animals' hunting strategies, it was re-modelled as a many-objective optimisation problem. In order to have realistic and applicable diet plans, cooked dishes are used. A well-known many-objective evolutionary algorithm is used to solve the diet problem. Results show that our approach can optimise specialised daily menus for different user types, depending on their preferences, age, gender and body index. Our approach can be easily adapted for users with health issues by adding new constraints and objectives. Our approach can be used individually or by dietitians as a decision support mechanism. Twit Text FOAVip Recommending healthy meal plans by optimising nature-inspired many-objective diet problem ????Health Informatics J http://www.kidney.de/pget.php?&tw=1&pmid=33438501 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33438501 #FOAvip English Wikipedia <ref>{{Cite pmid|33438501}}</ref> Recommending healthy meal plans by optimising nature-inspired many-objective diet problem #MMPMID33438501 Turkmenoglu C; Etaner Uyar AS; Kiraz B Health Informatics J 2021[Jan]; 27 (1): 1460458220976719 PMID33438501show ga Healthy eating is an important issue affecting a large part of the world population, so human diets are becoming increasingly popular, especially with the devastating consequences of Coronavirus Disease (Covid-19). A realistic and sustainable diet plan can help us to have a healthy eating habit since it considers most of the expectations from a diet without any restriction. In this study, the classical diet problem has been extended in terms of modelling, data sets and solution approach. Inspired by animals' hunting strategies, it was re-modelled as a many-objective optimisation problem. In order to have realistic and applicable diet plans, cooked dishes are used. A well-known many-objective evolutionary algorithm is used to solve the diet problem. Results show that our approach can optimise specialised daily menus for different user types, depending on their preferences, age, gender and body index. Our approach can be easily adapted for users with health issues by adding new constraints and objectives. Our approach can be used individually or by dietitians as a decision support mechanism. |*Algorithms[MESH] |*Energy Intake[MESH] |Adult[MESH] |Age Factors[MESH] |Aged[MESH] |Behavioral Sciences[MESH] |Body Mass Index[MESH] |COVID-19/*epidemiology[MESH] |Cooking/economics/methods[MESH] |Diet, Healthy/*methods/psychology[MESH] |Feeding Behavior/psychology[MESH] |Female[MESH] |Food Preferences[MESH] |Humans[MESH] |Male[MESH] |SARS-CoV-2[MESH] |Sex Factors[MESH] |Time Factors[MESH]Recommending healthy meal plans by optimising nature-inspired many-obj(epmc).pdf DeepDyve Pubget Overpricing