人工神经网络在军事通航图泛化中的应用

IF 0.4 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
K. Pokonieczny, Wojciech Dawid
{"title":"人工神经网络在军事通航图泛化中的应用","authors":"K. Pokonieczny, Wojciech Dawid","doi":"10.1080/23729333.2023.2231589","DOIUrl":null,"url":null,"abstract":"ABSTRACT Passability maps are cartographic studies that are generally used by commanders in order to plan military operations. Pursuant to standardisation documents, they are developed by marking passable, hardly passable and impassable (GO, SLOW GO and NO GO) areas. This article presents a methodology for the generalisation of passability maps that are created automatically. For this purpose, artificial neural networks (ANN) were used, and, specifically, a multilayer perceptron. Teaching the network consisted in presenting the neural network examples of manual generalisation of source maps. The paper describes the manner of preparing teaching data to train artificial neural networks and their implementation, which leads to the creation of the resulting maps. The maps were generated in multiple input configurations of teaching data, which allowed us to conduct comparisons of the obtained maps. Areas of various levels of passability generalised manually by the operator were compared to maps generated by the ANN. In order to test the consistency of maps, Moran’s I spatial autocorrelation coefficient was determined. The conducted tests allowed us to obtain the optimum parameters of the generalisation process. The proposed methodology is fully automated and may be applied to any source data in any chosen area.","PeriodicalId":36401,"journal":{"name":"International Journal of Cartography","volume":"11 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2023-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The application of artificial neural networks for the generalisation of military passability maps\",\"authors\":\"K. Pokonieczny, Wojciech Dawid\",\"doi\":\"10.1080/23729333.2023.2231589\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Passability maps are cartographic studies that are generally used by commanders in order to plan military operations. Pursuant to standardisation documents, they are developed by marking passable, hardly passable and impassable (GO, SLOW GO and NO GO) areas. This article presents a methodology for the generalisation of passability maps that are created automatically. For this purpose, artificial neural networks (ANN) were used, and, specifically, a multilayer perceptron. Teaching the network consisted in presenting the neural network examples of manual generalisation of source maps. The paper describes the manner of preparing teaching data to train artificial neural networks and their implementation, which leads to the creation of the resulting maps. The maps were generated in multiple input configurations of teaching data, which allowed us to conduct comparisons of the obtained maps. Areas of various levels of passability generalised manually by the operator were compared to maps generated by the ANN. In order to test the consistency of maps, Moran’s I spatial autocorrelation coefficient was determined. The conducted tests allowed us to obtain the optimum parameters of the generalisation process. The proposed methodology is fully automated and may be applied to any source data in any chosen area.\",\"PeriodicalId\":36401,\"journal\":{\"name\":\"International Journal of Cartography\",\"volume\":\"11 1\",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2023-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Cartography\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/23729333.2023.2231589\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Cartography","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/23729333.2023.2231589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

本文章由计算机程序翻译,如有差异,请以英文原文为准。
The application of artificial neural networks for the generalisation of military passability maps
ABSTRACT Passability maps are cartographic studies that are generally used by commanders in order to plan military operations. Pursuant to standardisation documents, they are developed by marking passable, hardly passable and impassable (GO, SLOW GO and NO GO) areas. This article presents a methodology for the generalisation of passability maps that are created automatically. For this purpose, artificial neural networks (ANN) were used, and, specifically, a multilayer perceptron. Teaching the network consisted in presenting the neural network examples of manual generalisation of source maps. The paper describes the manner of preparing teaching data to train artificial neural networks and their implementation, which leads to the creation of the resulting maps. The maps were generated in multiple input configurations of teaching data, which allowed us to conduct comparisons of the obtained maps. Areas of various levels of passability generalised manually by the operator were compared to maps generated by the ANN. In order to test the consistency of maps, Moran’s I spatial autocorrelation coefficient was determined. The conducted tests allowed us to obtain the optimum parameters of the generalisation process. The proposed methodology is fully automated and may be applied to any source data in any chosen area.
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
International Journal of Cartography
International Journal of Cartography Social Sciences-Geography, Planning and Development
CiteScore
1.40
自引率
0.00%
发文量
13
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信