Developing a neuro–fuzzy system to classify drainage sub-basins according to erosion processes on the Island of Lefkas, Greece

Q4 Earth and Planetary Sciences Revista de Geomorfologie Pub Date : 2018-12-28 DOI:10.21094/RG.2018.025
N. Evelpidou, T. Gournelos, A. Karkani, Eirini Kardara
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引用次数: 1

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).
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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
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)。
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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
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