Prediction modelling framework comparative analysis of dissolved oxygen concentration variations using support vector regression coupled with multiple feature engineering and optimization methods: A case study in China-Reference-Cited by-同舟云学术

Prediction modelling framework comparative analysis of dissolved oxygen concentration variations using support vector regression coupled with multiple feature engineering and optimization methods: A case study in China

Published:2023-02 Issue: Volume:146 Page:109845
ISSN:1470-160X
Container-title:Ecological Indicators
language:en
Short-container-title:Ecological Indicators

Author:

Nong Xizhi,Lai Cheng,Chen Lihua,Shao Dongguo,Zhang Chi,Liang Jiankui

Funder

National Natural Science Foundation of China

Guangxi Science and Technology Department

Wuhan University State Key Laboratory of Water Resources and Hydropower Engineering Science

Specific Research Project of Guangxi for Research Bases and Talents

Publisher

Elsevier BV

Subject

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

Reference96 articles.

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4. Optimized fuzzy inference system to enhance prediction accuracy for influent characteristics of a sewage treatment plant;Ansari;Sci. Total Environ.,2020

5. Environmental factors as indicators of dissolved oxygen concentration and zooplankton abundance: Deep learning versus traditional regression approach;Banerjee;Ecol. Indic.,2019

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