{"title":"基于改进蚁群算法的量子无线通信网络多跳传输研究","authors":"Xinyuan Mao, Min Nie, Guang Yang","doi":"10.1145/3573942.3573985","DOIUrl":null,"url":null,"abstract":"Firstly, an improved ant colony algorithm (QCANT) is proposed to optimize quantum connectivity, and the entanglement example distribution node deployment in quantum wireless multi-hop networks is studied and analyzed. On this basis, this paper combined genetic algorithm with improved ant colony algorithm (GA-QCANT), which can effectively alleviate the problem of low efficiency of ant colony algorithm due to the lack of initial pheromone. Simulation results show that both QCANT and GA-QCANT improves quantum connectivity significantly, and GA-QCANT improves quantum connectivity by an average of 32.1% compared to QCANT.","PeriodicalId":103293,"journal":{"name":"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Multi-hop Transmission in Quantum Wireless Communication Networks Based on Improved Ant Colony Algorithm\",\"authors\":\"Xinyuan Mao, Min Nie, Guang Yang\",\"doi\":\"10.1145/3573942.3573985\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Firstly, an improved ant colony algorithm (QCANT) is proposed to optimize quantum connectivity, and the entanglement example distribution node deployment in quantum wireless multi-hop networks is studied and analyzed. On this basis, this paper combined genetic algorithm with improved ant colony algorithm (GA-QCANT), which can effectively alleviate the problem of low efficiency of ant colony algorithm due to the lack of initial pheromone. Simulation results show that both QCANT and GA-QCANT improves quantum connectivity significantly, and GA-QCANT improves quantum connectivity by an average of 32.1% compared to QCANT.\",\"PeriodicalId\":103293,\"journal\":{\"name\":\"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2022 5th International Conference on Artificial Intelligence and Pattern Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3573942.3573985\",\"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 2022 5th International Conference on Artificial Intelligence and Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3573942.3573985","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Multi-hop Transmission in Quantum Wireless Communication Networks Based on Improved Ant Colony Algorithm
Firstly, an improved ant colony algorithm (QCANT) is proposed to optimize quantum connectivity, and the entanglement example distribution node deployment in quantum wireless multi-hop networks is studied and analyzed. On this basis, this paper combined genetic algorithm with improved ant colony algorithm (GA-QCANT), which can effectively alleviate the problem of low efficiency of ant colony algorithm due to the lack of initial pheromone. Simulation results show that both QCANT and GA-QCANT improves quantum connectivity significantly, and GA-QCANT improves quantum connectivity by an average of 32.1% compared to QCANT.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
