Combining multivariate statistical techniques and random forests model to assess and diagnose the trophic status of Poyang Lake in China-Reference-Cited by-同舟云学术

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Combining multivariate statistical techniques and random forests model to assess and diagnose the trophic status of Poyang Lake in China

Published:2017-12 Issue: Volume:83 Page:74-83
ISSN:1470-160X
Container-title:Ecological Indicators
language:en
Short-container-title:Ecological Indicators

Author:

Li Bing,Yang Guishan,Wan Rongrong,Hörmann Georg,Huang Jiacong,Fohrer Nicola,Zhang Lu

Funder

National Basic Research Program of China (973 Program)

National Scientific Foundation of China

Publisher

Elsevier BV

Subject

Ecology,Ecology, Evolution, Behavior and Systematics,General Decision Sciences

Reference58 articles.

1. Pattern recognition techniques for the evaluation of spatial and temporal variations in water quality. A case study: Suquı́a river basin (Córdoba-Argentina);Alberto;Water. Res.,2001

2. Random forest model and TRIX used in combination to assess and diagnose the trophic status of Bizerte Lagoon southern Mediterranean;Béjaoui;Ecol. Indic.,2016

3. Comparing predictive cyanobacterial models from temperate regions;Beaulieu;Can. J. Fish. Aquat. Sci.,2014

4. Random forests;Breiman;Mach. Learn.,2001

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