根据希腊莱夫卡斯岛的侵蚀过程,开发一种神经模糊系统对流域子盆地进行分类

Q4 Earth and Planetary Sciences
N. Evelpidou, T. Gournelos, A. Karkani, Eirini Kardara
{"title":"根据希腊莱夫卡斯岛的侵蚀过程,开发一种神经模糊系统对流域子盆地进行分类","authors":"N. Evelpidou, T. Gournelos, A. Karkani, Eirini Kardara","doi":"10.21094/RG.2018.025","DOIUrl":null,"url":null,"abstract":"In this paper we attempt to classify drainage sub-basins according to their erosion risk. We have adopted a multistep procedure to face this problem. The input variables were introduced into a GIS – platform. These variables were the vulnerability of the surface rocks to erosion, topographic variations, vegetation cover, land use and drainage basin characteristics. We constructed a fuzzy inference mechanism to pre-process the input variables. Next we used neural–network technology to process the input variables. The system was trained to ‘learn’ and classify the input data. The output of this procedure was a classification of the sub-drainage basins related to their risk of erosion. This neuro–fuzzy system was applied to the island of Lefkas (Greece).","PeriodicalId":52661,"journal":{"name":"Revista de Geomorfologie","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Developing a neuro–fuzzy system to classify drainage sub-basins according to erosion processes on the Island of Lefkas, Greece\",\"authors\":\"N. Evelpidou, T. Gournelos, A. Karkani, Eirini Kardara\",\"doi\":\"10.21094/RG.2018.025\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we attempt to classify drainage sub-basins according to their erosion risk. We have adopted a multistep procedure to face this problem. The input variables were introduced into a GIS – platform. These variables were the vulnerability of the surface rocks to erosion, topographic variations, vegetation cover, land use and drainage basin characteristics. We constructed a fuzzy inference mechanism to pre-process the input variables. Next we used neural–network technology to process the input variables. The system was trained to ‘learn’ and classify the input data. The output of this procedure was a classification of the sub-drainage basins related to their risk of erosion. This neuro–fuzzy system was applied to the island of Lefkas (Greece).\",\"PeriodicalId\":52661,\"journal\":{\"name\":\"Revista de Geomorfologie\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista de Geomorfologie\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21094/RG.2018.025\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Earth and Planetary Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista de Geomorfologie","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21094/RG.2018.025","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Earth and Planetary Sciences","Score":null,"Total":0}
引用次数: 1

摘要

本文试图根据侵蚀风险对流域进行分类。我们采取了多步骤处理这个问题。将输入变量引入到GIS平台中。这些变量包括地表岩石对侵蚀的脆弱性、地形变化、植被覆盖、土地利用和流域特征。构建了模糊推理机制对输入变量进行预处理。接下来,我们使用神经网络技术来处理输入变量。该系统被训练为“学习”并对输入数据进行分类。这一程序的结果是根据侵蚀风险对次流域进行分类。该神经模糊系统应用于Lefkas岛(希腊)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developing a neuro–fuzzy system to classify drainage sub-basins according to erosion processes on the Island of Lefkas, Greece
In this paper we attempt to classify drainage sub-basins according to their erosion risk. We have adopted a multistep procedure to face this problem. The input variables were introduced into a GIS – platform. These variables were the vulnerability of the surface rocks to erosion, topographic variations, vegetation cover, land use and drainage basin characteristics. We constructed a fuzzy inference mechanism to pre-process the input variables. Next we used neural–network technology to process the input variables. The system was trained to ‘learn’ and classify the input data. The output of this procedure was a classification of the sub-drainage basins related to their risk of erosion. This neuro–fuzzy system was applied to the island of Lefkas (Greece).
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
Revista de Geomorfologie
Revista de Geomorfologie Earth and Planetary Sciences-Computers in Earth Sciences
CiteScore
1.20
自引率
0.00%
发文量
0
审稿时长
10 weeks
×
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