{"title":"群智能算法综述","authors":"Suganya Selvaraj, Eunmi Choi","doi":"10.1145/3378936.3378977","DOIUrl":null,"url":null,"abstract":"Swarm Intelligence (SI) is an AI technique that has the collective behavior of a decentralized, self-organized system. SI has more advantages such as scalability, adaptability, collective robustness and individual simplicity and also has the ability to solve complex problems. Besides, SI algorithms also have few issues in time-critical applications, parameter tuning, and stagnation. SI algorithms need to be studied more to overcome these kinds of issues. In this paper, we studied a few popular algorithms in detail to identify important control parameters and randomized distribution. We also studied and summarized the performance comparison of SI algorithms in different applications.","PeriodicalId":304149,"journal":{"name":"Proceedings of the 3rd International Conference on Software Engineering and Information Management","volume":"92 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Survey of Swarm Intelligence Algorithms\",\"authors\":\"Suganya Selvaraj, Eunmi Choi\",\"doi\":\"10.1145/3378936.3378977\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Swarm Intelligence (SI) is an AI technique that has the collective behavior of a decentralized, self-organized system. SI has more advantages such as scalability, adaptability, collective robustness and individual simplicity and also has the ability to solve complex problems. Besides, SI algorithms also have few issues in time-critical applications, parameter tuning, and stagnation. SI algorithms need to be studied more to overcome these kinds of issues. In this paper, we studied a few popular algorithms in detail to identify important control parameters and randomized distribution. We also studied and summarized the performance comparison of SI algorithms in different applications.\",\"PeriodicalId\":304149,\"journal\":{\"name\":\"Proceedings of the 3rd International Conference on Software Engineering and Information Management\",\"volume\":\"92 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 3rd International Conference on Software Engineering and Information Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3378936.3378977\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Conference on Software Engineering and Information Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3378936.3378977","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Swarm Intelligence (SI) is an AI technique that has the collective behavior of a decentralized, self-organized system. SI has more advantages such as scalability, adaptability, collective robustness and individual simplicity and also has the ability to solve complex problems. Besides, SI algorithms also have few issues in time-critical applications, parameter tuning, and stagnation. SI algorithms need to be studied more to overcome these kinds of issues. In this paper, we studied a few popular algorithms in detail to identify important control parameters and randomized distribution. We also studied and summarized the performance comparison of SI algorithms in different applications.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
