{"title":"多目标营养膳食决策的组合量子粒子群优化算法","authors":"Youbo Lv","doi":"10.1109/ICCSIT.2009.5234580","DOIUrl":null,"url":null,"abstract":"A assembled method based on quantum particle swarm optimization (QPSO) algorithm combined with Bayesian networks (BN) is proposed to solve complex multi-objective nutritional diet decision making problem. To realize nutritional diet decision optimization for patients, BN model for dealing with associative relationship between diseases and diets is set up to compute and update the edibility of every food in database. QPSO algorithm is selected as the core optimization algorithm to avoid being trapped in a local optimum. Actual experimental results show that such combined method is a feasible and effective approach for actual nutritional diet decision making problem.","PeriodicalId":342396,"journal":{"name":"2009 2nd IEEE International Conference on Computer Science and Information Technology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Combined quantum particle swarm optimization algorithm for multi-objective nutritional diet decision making\",\"authors\":\"Youbo Lv\",\"doi\":\"10.1109/ICCSIT.2009.5234580\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A assembled method based on quantum particle swarm optimization (QPSO) algorithm combined with Bayesian networks (BN) is proposed to solve complex multi-objective nutritional diet decision making problem. To realize nutritional diet decision optimization for patients, BN model for dealing with associative relationship between diseases and diets is set up to compute and update the edibility of every food in database. QPSO algorithm is selected as the core optimization algorithm to avoid being trapped in a local optimum. Actual experimental results show that such combined method is a feasible and effective approach for actual nutritional diet decision making problem.\",\"PeriodicalId\":342396,\"journal\":{\"name\":\"2009 2nd IEEE International Conference on Computer Science and Information Technology\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 2nd IEEE International Conference on Computer Science and Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSIT.2009.5234580\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd IEEE International Conference on Computer Science and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSIT.2009.5234580","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Combined quantum particle swarm optimization algorithm for multi-objective nutritional diet decision making
A assembled method based on quantum particle swarm optimization (QPSO) algorithm combined with Bayesian networks (BN) is proposed to solve complex multi-objective nutritional diet decision making problem. To realize nutritional diet decision optimization for patients, BN model for dealing with associative relationship between diseases and diets is set up to compute and update the edibility of every food in database. QPSO algorithm is selected as the core optimization algorithm to avoid being trapped in a local optimum. Actual experimental results show that such combined method is a feasible and effective approach for actual nutritional diet decision making problem.