Comparing artificial intelligence techniques for chlorophyll-a prediction in US lakes

Chlorophyll-a (CHLA) is a key indicator to represent eutrophication status in lakes. In this study, CHLA, total phosphorus (TP), total nitrogen (TN), turbidity (TB), and Secchi depth (SD) collected by the United States Environmental Protection Agency for the National Lakes Assessment in the continen...

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Veröffentlicht in:	Environmental science and pollution research international 2019-10, Vol.26 (29), p.30524-30532
Hauptverfasser:	Luo, Wenguang, Zhu, Senlin, Wu, Shiqiang, Dai, Jiangyu
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptive systems Algorithms Anthropogenic factors Aquatic ecosystems Aquatic Pollution Artificial Intelligence Artificial lakes Artificial neural networks Atmospheric Protection/Air Quality Control/Air Pollution Chlorophyll Chlorophyll - analysis Chlorophyll A - analysis Cluster Analysis Clustering Earth and Environmental Science Ecosystem Ecotoxicology Environment Environmental Chemistry Environmental Health Environmental Monitoring - methods Environmental protection Environmental science Eutrophication Fuzzy logic Fuzzy systems Lakes Lakes - analysis Lakes - chemistry Model accuracy Multilayer perceptrons Neural networks Nitrogen - analysis Perturbation Phosphorus Phosphorus - analysis Short Research and Discussion Article Statistical analysis Turbidity United States United States Environmental Protection Agency Waste Water Technology Water Management Water Pollution Control Water Quality
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