基于置信函数的GPS测量问题准则间分析

2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA) Pub Date : 2019-07-01 DOI:10.1109/INISTA.2019.8778423

S. Fidanova, J. Dezert, A. Tchamova

{"title":"基于置信函数的GPS测量问题准则间分析","authors":"S. Fidanova, J. Dezert, A. Tchamova","doi":"10.1109/INISTA.2019.8778423","DOIUrl":null,"url":null,"abstract":"In this paper we present an application of a new Belief Function-based Inter-Criteria Analysis (BF-ICrA) approach for Global Positioning System (GPS) Surveying Problems (GSP). GPS surveying is an NP-hard problem. For designing Global Positioning System surveying network, a given set of earth points must be observed consecutively. The survey cost is the sum of the distances to go from one point to another one. This kind of problems is hard to be solved with traditional numerical methods. In this paper we use BF-ICrA to analyze an Ant Colony Optimization (ACO) algorithm developed to provide near-optimal solutions for Global Positioning System surveying problem.","PeriodicalId":262143,"journal":{"name":"2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Inter-Criteria Analysis Based on Belief Functions for GPS Surveying Problems\",\"authors\":\"S. Fidanova, J. Dezert, A. Tchamova\",\"doi\":\"10.1109/INISTA.2019.8778423\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present an application of a new Belief Function-based Inter-Criteria Analysis (BF-ICrA) approach for Global Positioning System (GPS) Surveying Problems (GSP). GPS surveying is an NP-hard problem. For designing Global Positioning System surveying network, a given set of earth points must be observed consecutively. The survey cost is the sum of the distances to go from one point to another one. This kind of problems is hard to be solved with traditional numerical methods. In this paper we use BF-ICrA to analyze an Ant Colony Optimization (ACO) algorithm developed to provide near-optimal solutions for Global Positioning System surveying problem.\",\"PeriodicalId\":262143,\"journal\":{\"name\":\"2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INISTA.2019.8778423\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INISTA.2019.8778423","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 2

摘要

本文提出了一种新的基于信念函数的标准间分析(BF-ICrA)方法在全球定位系统(GPS)测量问题(GSP)中的应用。GPS测量是NP-hard问题。在设计全球定位系统测量网时，必须对给定的一组地球点进行连续观测。测量成本是从一点到另一点的距离的总和。这类问题是传统数值方法难以解决的。本文利用BF-ICrA分析了一种为全球定位系统测量问题提供近最优解的蚁群优化算法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Inter-Criteria Analysis Based on Belief Functions for GPS Surveying Problems

In this paper we present an application of a new Belief Function-based Inter-Criteria Analysis (BF-ICrA) approach for Global Positioning System (GPS) Surveying Problems (GSP). GPS surveying is an NP-hard problem. For designing Global Positioning System surveying network, a given set of earth points must be observed consecutively. The survey cost is the sum of the distances to go from one point to another one. This kind of problems is hard to be solved with traditional numerical methods. In this paper we use BF-ICrA to analyze an Ant Colony Optimization (ACO) algorithm developed to provide near-optimal solutions for Global Positioning System surveying problem.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA)

自引率

0.00%

发文量