Predicting coastal algal blooms with environmental factors by machine learning methods-Reference-Cited by-同舟云学术

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Predicting coastal algal blooms with environmental factors by machine learning methods

Published:2021-04 Issue: Volume:123 Page:107334
ISSN:1470-160X
Container-title:Ecological Indicators
language:en
Short-container-title:Ecological Indicators

Author:

Yu Peixuan,Gao Rui,Zhang Dezhen,Liu Zhi-Ping

Funder

Major Scientific and Technological Innovation Project of Shandong Province

National Natural Science Foundation of China

National Natural Science Foundation of China-Shandong Joint Fund

Publisher

Elsevier BV

Subject

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

Reference33 articles.

1. Harmful algal blooms and eutrophication: Nutrient sources, composition, and consequences;Anderson;Estuaries,2002

2. Excessive nitrogen and phosphorus in European rivers: 2000–2050;Blaas;Ecol. Indicators,2016

3. Breiman, L. 2017. Classification and Regression Trees. Routledge.

4. Use of principal component scores in multiple linear regression models for prediction of Chlorophyll-a in reservoirs;Çamdevýren;Ecol. Model.,2005

5. Support-vector networks;Cortes;Mach. Learn.,1995

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