{"title":"航空运输无处不在世界中的应用数据挖掘方法","authors":"Saybani Mahmoud Reza, T. Wah, A. Lahsasna","doi":"10.1109/ICCIT.2009.255","DOIUrl":null,"url":null,"abstract":"Noise is a big problem for people living near airports, therefore the public, airport authorities and pilots are looking for ways to reduce the noise in the vicinity of populated areas. Optimal solution would be flight paths that are farthest from those areas, and worst paths are those, that just go above them. There are two classes of paths, namely optimal and non-optimal ones. This paper is going to use one of successfully used data mining techniques, namely neural network, which is capable of recognizing patterns. We used some coordinates of various flight paths as input for learning purposes of Neural Network, and defined two classes representing the optimal and non-optimal flight paths. The results have shown that this technique is well capable of recognizing the optimal and non-optimal flight paths. This technique can be used to reduce the noise.","PeriodicalId":112416,"journal":{"name":"2009 Fourth International Conference on Computer Sciences and Convergence Information Technology","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Applied Data Mining Approach in Ubiquitous World of Air Transportation\",\"authors\":\"Saybani Mahmoud Reza, T. Wah, A. Lahsasna\",\"doi\":\"10.1109/ICCIT.2009.255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Noise is a big problem for people living near airports, therefore the public, airport authorities and pilots are looking for ways to reduce the noise in the vicinity of populated areas. Optimal solution would be flight paths that are farthest from those areas, and worst paths are those, that just go above them. There are two classes of paths, namely optimal and non-optimal ones. This paper is going to use one of successfully used data mining techniques, namely neural network, which is capable of recognizing patterns. We used some coordinates of various flight paths as input for learning purposes of Neural Network, and defined two classes representing the optimal and non-optimal flight paths. The results have shown that this technique is well capable of recognizing the optimal and non-optimal flight paths. This technique can be used to reduce the noise.\",\"PeriodicalId\":112416,\"journal\":{\"name\":\"2009 Fourth International Conference on Computer Sciences and Convergence Information Technology\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Fourth International Conference on Computer Sciences and Convergence Information Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIT.2009.255\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fourth International Conference on Computer Sciences and Convergence Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIT.2009.255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Applied Data Mining Approach in Ubiquitous World of Air Transportation
Noise is a big problem for people living near airports, therefore the public, airport authorities and pilots are looking for ways to reduce the noise in the vicinity of populated areas. Optimal solution would be flight paths that are farthest from those areas, and worst paths are those, that just go above them. There are two classes of paths, namely optimal and non-optimal ones. This paper is going to use one of successfully used data mining techniques, namely neural network, which is capable of recognizing patterns. We used some coordinates of various flight paths as input for learning purposes of Neural Network, and defined two classes representing the optimal and non-optimal flight paths. The results have shown that this technique is well capable of recognizing the optimal and non-optimal flight paths. This technique can be used to reduce the noise.