Relative performance of different data mining techniques for nitrate concentration and load estimation in different type of watersheds-Reference-Cited by-同舟云学术

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Relative performance of different data mining techniques for nitrate concentration and load estimation in different type of watersheds

Published:2020-08 Issue: Volume:263 Page:114618
ISSN:0269-7491
Container-title:Environmental Pollution
language:en
Short-container-title:Environmental Pollution

Author:

Li Shiyang,Bhattarai Rabin,Cooke Richard A.,Verma Siddhartha,Huang Xiangfeng,Markus Momcilo,Christianson Laura

Funder

U.S. Department of Agriculture

China Postdoctoral Science Foundation

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Pollution,Toxicology,General Medicine

Reference54 articles.

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2. Using of neural networks for the prediction of nitrate groundwater contamination in rural and agricultural areas;Al-Mahallawi;Environ. Earth Sci.,2012

3. Modelling the spatial and seasonal variability of water quality for entire river networks: relationships with natural and anthropogenic factors;Álvarez-Cabria;Sci. Total Environ.,2016

4. A neural network experiment on the simulation of daily nitrate-nitrogen and suspended sediment fluxes from a small agricultural catchment;Anctil;Ecol. Model.,2009

5. Vertical stratification of soil phosphorus as a concern for dissolved phosphorus runoff in the lake Erie basin;Baker;J. Environ. Qual.,2017

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