{"title":"基于鱼类生物学的鱼类洄游优化","authors":"Jeng-Shyang Pan, Pei-wei Tsai, Yu-Bin Liao","doi":"10.1109/ICGEC.2010.198","DOIUrl":null,"url":null,"abstract":"In this paper, we propose Fish Migration Optimization (FMO) method based on a verified equation of the fish swim in the fish biology for solving numerical optimization problems. Inspired by the fish migration, the migration and the swim model are integrated into the optimization process. Four benchmark functions are used to test the convergence, the accuracy and the speed of FMO, and the experimental results are compared with PSO. The experimental result indicates that the proposed FMO presents higher accuracy and convergence speed.","PeriodicalId":373949,"journal":{"name":"2010 Fourth International Conference on Genetic and Evolutionary Computing","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"Fish Migration Optimization Based on the Fishy Biology\",\"authors\":\"Jeng-Shyang Pan, Pei-wei Tsai, Yu-Bin Liao\",\"doi\":\"10.1109/ICGEC.2010.198\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose Fish Migration Optimization (FMO) method based on a verified equation of the fish swim in the fish biology for solving numerical optimization problems. Inspired by the fish migration, the migration and the swim model are integrated into the optimization process. Four benchmark functions are used to test the convergence, the accuracy and the speed of FMO, and the experimental results are compared with PSO. The experimental result indicates that the proposed FMO presents higher accuracy and convergence speed.\",\"PeriodicalId\":373949,\"journal\":{\"name\":\"2010 Fourth International Conference on Genetic and Evolutionary Computing\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"32\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Fourth International Conference on Genetic and Evolutionary Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICGEC.2010.198\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Fourth International Conference on Genetic and Evolutionary Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICGEC.2010.198","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fish Migration Optimization Based on the Fishy Biology
In this paper, we propose Fish Migration Optimization (FMO) method based on a verified equation of the fish swim in the fish biology for solving numerical optimization problems. Inspired by the fish migration, the migration and the swim model are integrated into the optimization process. Four benchmark functions are used to test the convergence, the accuracy and the speed of FMO, and the experimental results are compared with PSO. The experimental result indicates that the proposed FMO presents higher accuracy and convergence speed.
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