Artificial neural networks as an indicator search engine: The visualization of natural and man-caused taxa variability
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- 作者：Djuradj Milo&scaron ; evića ; djuradj@pmf.ni.ac.rs" class="auth_mail" title="E-mail the corresponding author ; Dubravka Čerbab ; Jó ; zsef Szekeresc ; Bela Csá ; nyic ; Bojana Tubićd ; Vladica Simiće ; Momir Paunovićd
- 关键词：Chironomidae larvae ; Bioassessment ; Geo-SOM method ; Large river
- 刊名：Ecological Indicators
- 出版年：2016
- 出版时间：February 2016
- 年：2016
- 卷：61
- 期：part_P2
- 页码：777-789
- 全文大小：3468 K
文摘
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The SOM revealed factors responsible for the structuring of Chironomidae community.
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The Geo-SOM defined stressor-specific indicator taxa.
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The Geo-SOM visualized all obtained variability within indicator distributions.
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The type of substrate is one of the main generators of the natural variability.