{"title":"一种基于粒子群优化的路网匹配方法","authors":"F. Zhu, Peng-Zhong Wang","doi":"10.1145/3318265.3318282","DOIUrl":null,"url":null,"abstract":"With the complexity of spatial object matching between multi-source and multi-scale road networks is increasing, road network space target matching method encountered different levels of bottleneck in precision and accuracy. This paper proposes a road network matching method based on the stable spatial hierarchical structure, this method has both global and local features, it can overcome the mismatch caused by excessive dependence on local morphological structure as similarity criterion, and the matching result can also be found by fast convergence. The experimental results show that this paper combines particle swarm optimization for road network matching, it has obvious advantages in regions with similar local structures and significant global structural differences, the matching accuracy and optimization efficiency are improved obviously.","PeriodicalId":241692,"journal":{"name":"Proceedings of the 3rd International Conference on High Performance Compilation, Computing and Communications","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A road network matching method based on particle swarm optimization\",\"authors\":\"F. Zhu, Peng-Zhong Wang\",\"doi\":\"10.1145/3318265.3318282\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the complexity of spatial object matching between multi-source and multi-scale road networks is increasing, road network space target matching method encountered different levels of bottleneck in precision and accuracy. This paper proposes a road network matching method based on the stable spatial hierarchical structure, this method has both global and local features, it can overcome the mismatch caused by excessive dependence on local morphological structure as similarity criterion, and the matching result can also be found by fast convergence. The experimental results show that this paper combines particle swarm optimization for road network matching, it has obvious advantages in regions with similar local structures and significant global structural differences, the matching accuracy and optimization efficiency are improved obviously.\",\"PeriodicalId\":241692,\"journal\":{\"name\":\"Proceedings of the 3rd International Conference on High Performance Compilation, Computing and Communications\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 3rd International Conference on High Performance Compilation, Computing and Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3318265.3318282\",\"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 High Performance Compilation, Computing and Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3318265.3318282","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A road network matching method based on particle swarm optimization
With the complexity of spatial object matching between multi-source and multi-scale road networks is increasing, road network space target matching method encountered different levels of bottleneck in precision and accuracy. This paper proposes a road network matching method based on the stable spatial hierarchical structure, this method has both global and local features, it can overcome the mismatch caused by excessive dependence on local morphological structure as similarity criterion, and the matching result can also be found by fast convergence. The experimental results show that this paper combines particle swarm optimization for road network matching, it has obvious advantages in regions with similar local structures and significant global structural differences, the matching accuracy and optimization efficiency are improved obviously.