{"title":"基于分割的网格图优化","authors":"Erhan Bülbül Ösym, Türkiye Ankara, Aydın Çetin","doi":"10.1109/IDAP.2017.8090173","DOIUrl":null,"url":null,"abstract":"This work examines the effects of reducing the number of nodes and edges in a grid-graph, which consists of heterogeneous node blocks. An optimization method that reduces the count of nodes and edges is presented. Approaches that make traversing the graph easier by using this method are explained with examples. Efficiency of the method is observed using different pathfinding algorithms.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimization of Grid-Graphs using Segmentation\",\"authors\":\"Erhan Bülbül Ösym, Türkiye Ankara, Aydın Çetin\",\"doi\":\"10.1109/IDAP.2017.8090173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work examines the effects of reducing the number of nodes and edges in a grid-graph, which consists of heterogeneous node blocks. An optimization method that reduces the count of nodes and edges is presented. Approaches that make traversing the graph easier by using this method are explained with examples. Efficiency of the method is observed using different pathfinding algorithms.\",\"PeriodicalId\":111721,\"journal\":{\"name\":\"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IDAP.2017.8090173\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IDAP.2017.8090173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This work examines the effects of reducing the number of nodes and edges in a grid-graph, which consists of heterogeneous node blocks. An optimization method that reduces the count of nodes and edges is presented. Approaches that make traversing the graph easier by using this method are explained with examples. Efficiency of the method is observed using different pathfinding algorithms.